U.S. patent application number 16/036921 was filed with the patent office on 2019-05-09 for system and method for sensor-based determination of user role, location, and/or state of one or more in-vehicle mobile device and enforcement of usage thereof.
The applicant listed for this patent is Cellepathy Inc.. Invention is credited to Dan Abramson, Yuval Kashtan, Andrei Kolin, Itzhak Pomerantz, Guy Soffer.
Application Number | 20190141489 16/036921 |
Document ID | / |
Family ID | 45874366 |
Filed Date | 2019-05-09 |
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United States Patent
Application |
20190141489 |
Kind Code |
A1 |
Abramson; Dan ; et
al. |
May 9, 2019 |
SYSTEM AND METHOD FOR SENSOR-BASED DETERMINATION OF USER ROLE,
LOCATION, AND/OR STATE OF ONE OR MORE IN-VEHICLE MOBILE DEVICE AND
ENFORCEMENT OF USAGE THEREOF
Abstract
Systems and methods are disclosed for computing various
determinations at one or more mobile devices and/or central
machines. In part, such determinations are computed based on
analysis of one or more inputs originating at one or more sensors
of one or more devices. Such determinations include determining an
in-vehicle role, an in-vehicle location, a handheld state, and a
vehicle class. Various transformations, modifications, and outputs
can result from such determinations. Also disclosed are systems and
methods for restricting operation of a mobile device, including
restrictions that impede operation by a driver moreso than
operation by a passenger. Also disclosed are systems and methods
for orienting a coordinate system of a mobile device.
Inventors: |
Abramson; Dan; (SAMMAMISH,
WA) ; Pomerantz; Itzhak; (Kfar Saba, IL) ;
Kashtan; Yuval; (Mishmeret, IL) ; Kolin; Andrei;
(Herzliya, IL) ; Soffer; Guy; (Karkur,
IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Cellepathy Inc. |
Sammamish |
WA |
US |
|
|
Family ID: |
45874366 |
Appl. No.: |
16/036921 |
Filed: |
July 16, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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|
14792546 |
Jul 6, 2015 |
10028113 |
|
|
16036921 |
|
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|
|
14298953 |
Jun 8, 2014 |
9078116 |
|
|
14792546 |
|
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|
13825527 |
Jul 29, 2013 |
8750853 |
|
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PCT/US2011/052655 |
Sep 21, 2011 |
|
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|
14298953 |
|
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|
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61427228 |
Dec 27, 2010 |
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61384726 |
Sep 21, 2010 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04W 8/18 20130101; H04W
4/48 20180201; H04M 2250/10 20130101; H04M 2250/12 20130101; H04L
67/12 20130101; H04W 4/40 20180201; H04W 12/0802 20190101; H04M
1/72577 20130101; H04W 4/14 20130101; H04W 64/006 20130101; H04W
4/80 20180201; H04W 64/003 20130101; H04M 1/6091 20130101 |
International
Class: |
H04W 4/14 20060101
H04W004/14; H04W 4/80 20060101 H04W004/80; H04W 8/18 20060101
H04W008/18; H04W 4/40 20060101 H04W004/40; H04L 29/08 20060101
H04L029/08; H04W 64/00 20060101 H04W064/00; H04M 1/725 20060101
H04M001/725 |
Claims
1. An in-vehicle determination system for adjusting an operation of
a first mobile device, the system comprising: a processor; a
control circuit operatively connected to the processor; a memory
operatively connected to the control circuit and accessible by the
processor; and a determination module stored in the memory and
executable in the processor; and at least one of: a user interface
stored in the memory and executing in the processor; an operating
system stored in the memory and executing in the processor, an
accelerometer operatively connected to the control circuit, a
gyroscope operatively connected to the control circuit, a GPS
receiver operatively connected to the control circuit, a microphone
operatively connected to the control circuit, a magnetometer
operatively connected to the control circuit, a camera operatively
connected to the control circuit, a light sensor operatively
connected to the control circuit, a temperature sensor operatively
connected to the control circuit, an altitude sensor operatively
connected to the control circuit, a pressure sensor operatively
connected to the control circuit, a proximity sensor operatively
connected to the control circuit, a near-field communication (NFC)
device operatively connected to the control circuit, a compass
operatively connected to the control circuit; and a communications
interface operatively connected to the control circuit; wherein the
determination module, when executed by the processor, configures
the control circuit to: receive a first input from at least one of
the user interface, the operating system, the accelerometer, the
gyroscope, the GPS receiver, the microphone, the magnetometer, the
camera, the light sensor, the temperature sensor, the altitude
sensor, the pressure sensor, the proximity sensor, the NFC device,
the compass, and the communications interface of the first mobile
device, the first input originating from an identifying event
perceptible to at least one of the user interface, the operating
system, the accelerometer, the gyroscope, the GPS receiver, the
microphone, the magnetometer, the camera, the light sensor, the
temperature sensor, the altitude sensor, the pressure sensor, the
proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device; analyze the
first input with the determination module to identify one or more
determination characteristics within the first input; compute at
least one determination factor based on the one or more
determination characteristics, the at least one determination
factor pertaining to at least one of (a) at least one aspect of the
in-vehicle role of the user; and (b) at least one aspect of an
in-vehicle location of the mobile device; and at least one of (a)
transform at least one operation state of the first mobile device
based on the at least one determination factor, (b) output at least
one operation state based on the at least one determination factor,
(c) output at least one in-vehicle role of the user based on at
least one determination factor; (d) output at least one in-vehicle
location of the mobile device based on at least one determination
factor and (e) output at least one result based on the at least one
determination factor.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 14/792,546, filed Jul. 6, 2015 (now U.S. Pat.
No. 10,028,113) which is a continuation of U.S. patent application
Ser. No. 14/298,953, filed Jun. 8, 2014 (now U.S. Pat. No.
9,078,116), which is a continuation of U.S. patent application Ser.
No. 13/825,527, filed Jul. 29, 2013 (now U.S. Pat. No. 8,750,853)
which is a US National Stage Application of International
Application No. PCT/US2011/052655, filed Sep. 21, 2011, which
claims the benefit of U.S. Patent Application No. 61/427,228, filed
Dec. 27, 2010, and U.S. Patent Application No. 61/384,726, filed
Sep. 21, 2010, each of which is hereby incorporated by reference in
its respective entirety.
TECHNICAL FIELD OF THE INVENTION
[0002] This disclosure relates generally to the field of mobile
device identification, and, in particular, to computer-implemented
systems and methods for determining roles and usages of a mobile
device within a vehicle.
BACKGROUND OF THE INVENTION
[0003] There are approximately 4.6 billion cellular phone
subscriptions in the world over which it is estimated that more
than 2 trillion text (SMS) messages are sent annually. There are
also over 800 million transportation vehicles in the world. The
magnitude of these statistics indicates that cellular phone use in
vehicles is inevitable and is likely to remain quite common, unless
preventative measures are taken.
[0004] Drivers using a hand-held cellular phone or smartphone for
talking, text messaging, and/or for executing other applications or
`apps` while driving has become a problem of near-epidemic
proportions. Studies on distracted driving have shown that by
talking on a cell phone, a driver increases his/her risk of an
accident by a factor of four. Even worse, sending text messages
increases a driver's accident risk 23-fold. Additionally, studies
have shown that the temptation to use a cellular phone for texting,
talking, and other activities while operating a vehicle is not
limited to younger drivers--adult drivers have been shown to text
more often than younger ones.
[0005] In response to this growing concern and danger, numerous
regulatory actions have been put in place to attempt to mitigate
such phone-based distractions to drivers. For example, in the
United States, thirty states have banned drivers of vehicles from
texting, and many have subsequently increased the penalties for
such violations. Driving-while-texting has also been banned
throughout Europe and many other countries around the world.
Additionally, talking on a hand-held cellular phone while driving a
vehicle has been banned in eight US states, and such cell phone use
has been banned in all of Europe and in many other countries.
[0006] The effectiveness of these laws alone, without an effective
means of enforcement, is questionable. Being that cellular phones
are generally small and discreet and drivers are frequently in
motion, it is often difficult for law enforcement personnel to
effectively police for such violations. Indeed, statistics show
that accidents arising from cellular phone-based distractions are
increasing as the popularity of such devices increases.
[0007] Given the easy accessibility of cell phones to drivers, many
drivers' apparent desire to operate their cellular phones while
driving, and the difficulties attendant with enforcing laws
prohibiting cellular phone use, it is likely that drivers will
continue to use cellular phones for texting, talking, and/or other
activities (e.g., playing games or running applications), for the
foreseeable future.
[0008] Several solutions have been proposed to address
illegal/unsafe cell phone usage by drivers of vehicles. Certain of
these approaches seek to utilize a phone's on-board GPS and/or
accelerometers to establish the likelihood that the phone is being
used within a moving vehicle. If the data extracted from the GPS
and/or the accelerometers indicates that the vehicle is moving,
then the software in the cell phone deactivates "risky" cell phone
functions or otherwise thwarts cell phone-based distractions (such
solutions are commonly known as "blocking" solutions).
[0009] However, such solutions are incapable of distinguishing
between the driver of a vehicle and a passenger in the same vehicle
who should retain the right to use his/her cellular phone. There
are various common driving scenarios where it would be advantageous
for a passenger to use his/her cellular phone (such as to obtain
driving directions). As such, the proposed "blocking" solutions
entail substantial and critical shortcomings, as they often
unnecessarily block a passenger's ability to use their cellular
phone within a moving vehicle. This challenge of distinguishing
between a passenger and a driver in a moving vehicle is commonly
referred to as the "Passenger Problem".
[0010] Other solutions addressing this problem of cellular phone
use while driving require the pre-installation of a hardware device
in the vehicle. Such devices are typically installed next to the
driver and are used to transmit a short distance blocking signal,
effectively creating a no-use zone around the driver's location
within the car. Such devices prevent the driver (or anyone located
within the no-use zone) from using a cellular phone by effectively
deactivating the phone. However, such approaches are onerous in
that they require that car-owners purchase and install the
requisite additional hardware, creating significant impediments for
widespread adoption. In addition, the costs of manufacturing and
installing such hardware are rather high--approximately $100-$200
per cellular phone.
[0011] Yet other proposed solutions attempt to address the problem
of cellular phone use while driving by utilizing text-to-voice
technology, whereby email and text messages are spoken for the user
(presumably the driver) while in a moving vehicle. However, such
solutions also suffer from the Passenger Problem, i.e., the
text-to-voice application does not know how to distinguish drivers
(for whom the messages should be spoken) from passengers (for whom
they should not be spoken). As such, substantial confusion can
arise in a moving car with several passengers carrying cellular
phones. In such a scenario, each of the cellular phones of the
various passengers will recite the messages received by the
respective phone, since such solutions also cannot distinguish
between the cellular phone of the driver and the phones of the
passengers.
[0012] In addition, other proposed solutions seek to block all
texting and/or other applications by administering a small test or
puzzle to the user. The time that it takes the user to solve to the
test/puzzle can dictate whether the user is a driver or a
passenger. However, it can be readily appreciated that such an
approach, paradoxically, further distracts a driver who attempts to
use his/her cellular phone while driving, rather than actually
increasing the driver's safety.
[0013] It is with respect to these and other considerations that
the disclosure made herein is presented.
SUMMARY OF THE INVENTION
[0014] Technologies are presented herein in support of a system and
method for determining an in-vehicle role of a user of a mobile
device. According to one aspect, an in-vehicle determination system
for adjusting an operation of a first mobile device is provided.
The system includes a processor, a control circuit operatively
connected to the processor, a memory operatively connected to the
control circuit and accessible by the processor, and a
determination module stored in the memory and executable in the
processor, and at least one of: a user interface stored in the
memory and executing in the processor, an operating system stored
in the memory and executing in the processor, an accelerometer
operatively connected to the control circuit, a gyroscope
operatively connected to the control circuit, a GPS receiver
operatively connected to the control circuit, a microphone
operatively connected to the control circuit, a magnetometer
operatively connected to the control circuit, a camera operatively
connected to the control circuit, a light sensor operatively
connected to the control circuit, a temperature sensor operatively
connected to the control circuit, an altitude sensor operatively
connected to the control circuit, a pressure sensor operatively
connected to the control circuit, a proximity sensor operatively
connected to the control circuit, a near-field communication (NFC)
device operatively connected to the control circuit, a compass
operatively connected to the control circuit, and a communications
interface operatively connected to the control circuit. The
determination module, when executed by the processor, configures
the control circuit to receive a first input from at least one of
the user interface, the operating system, the accelerometer, the
gyroscope, the GPS receiver, the microphone, the magnetometer, the
camera, the light sensor, the temperature sensor, the altitude
sensor, the pressure sensor, the proximity sensor, the NFC device,
the compass, and the communications interface of the first mobile
device, the first input originating from an identifying event
perceptible to at least one of the user interface, the operating
system, the accelerometer, the gyroscope, the GPS receiver, the
microphone, the magnetometer, the camera, the light sensor, the
temperature sensor, the altitude sensor, the pressure sensor, the
proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device, analyze the
first input with the determination module to identify one or more
determination characteristics within the first input, and compute
at least one determination factor based on the one or more
determination characteristics, the at least one determination
factor pertaining to at least one of (a) at least one aspect of the
in-vehicle role of the user; and (b) at least one aspect of an
in-vehicle location of the mobile device. The determination module
further configures the control circuit to at least one of (a)
transform at least one operation state of the first mobile device
based on the at least one determination factor, (b) output at least
one operation state based on the at least one determination factor,
(c) output at least one in-vehicle role of the user based on at
least one determination factor, (d) output at least one in-vehicle
location of the mobile device based on at least one determination
factor, and (e) output at least one result based on the at least
one determination factor.
[0015] According to another aspect, a computer-implemented method
for determining at least one of (a) an in-vehicle role of a user;
and (b) an in-vehicle location of a first mobile device is
provided, the first mobile device having a processor, a memory, a
determination module stored in the memory and executable by the
processor, and at least one of a user interface, an operating
system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes receiving a first
input from at least one of the user interface, the operating
system, the accelerometer, the gyroscope, the GPS receiver, the
microphone, the magnetometer, the camera, the light sensor, the
temperature sensor, the altitude sensor, the pressure sensor, the
proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device, the first
input originating from one or more identifying events perceptible
to at least one of the user interface, the operating system, the
accelerometer, the gyroscope, the GPS receiver, the microphone, the
magnetometer, the camera, the light sensor, the temperature sensor,
the altitude sensor, the pressure sensor, the proximity sensor, the
NFC device, the compass, and the communications interface of the
first mobile device, analyzing the first input with the
determination module executing at the processor to identify one or
more determination characteristics within the first input, and
computing at least one determination factor based on the one or
more determination characteristics, the at least one determination
factor pertaining to at least one of (a) at least one aspect of the
in-vehicle role of the user; and (b) at least one aspect of an
in-vehicle location of the mobile device. The method further
includes at least one of (a) transforming at least one operation
state of the first mobile device based on the at least one
determination factor, (b) outputting at least one operation state
based on the at least one determination factor, (c) outputting at
least one in-vehicle role of the user based on at least one
determination factor; (d) outputting at least one in-vehicle
location of the mobile device based on at least one determination
factor and (e) outputting at least one result based on the at least
one determination factor.
[0016] According to another aspect, a computer-implemented method
for determining at least one of (a) an in-vehicle role of a user of
a first mobile device (b) an in-vehicle location of a first mobile
device, (c) a handheld state of the first mobile device, and (d)
one or more characteristics of the first mobile device is provided,
the first mobile device having a processor, a memory, and a
determination module stored in the memory and executable by the
processor, and at least one of a user interface, an operating
system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes receiving at least a
first input from at least one of the user interface, the operating
system, the accelerometer, the gyroscope, the GPS receiver, the
microphone, the magnetometer, the camera, the light sensor, the
temperature sensor, the altitude sensor, the pressure sensor, the
proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device, the first
input originating from an identifying event perceptible to at least
one of the user interface, the operating system, the accelerometer,
the gyroscope, the GPS receiver, the microphone, the magnetometer,
the camera, the light sensor, the temperature sensor, the altitude
sensor, the pressure sensor, the proximity sensor, the NFC device,
the compass, and the communications interface of the first mobile
device, analyzing at least the first input with the determination
module executing at the processor to identify at least one of one
or more determination characteristics and one or more handheld
state characteristics within the first input, and computing at
least one determination factor based on at least one of the at
least one of one or more determination characteristics and one or
more handheld state characteristics, the at least one determination
factor pertaining to at least one of (a) at least one aspect of the
in-vehicle role of the user, (b) at least one aspect of an
in-vehicle location of the mobile device, and (c) at least one
aspect of the handheld state of the mobile device. The method
further includes at least one of (a) modifying at least one
operation state, (b) outputting at least one operation state, (c)
outputting at least one in-vehicle role of the user, (d) outputting
at least one in-vehicle location, (e) outputting one or more
results, and (f) outputting the handheld state, of the first mobile
device based on the at least one determination factor.
[0017] According to another aspect, a computer-implemented method
for determining a vehicle class of a vehicle using a first mobile
device is provided, the first mobile device having a processor, a
memory, a determination module stored in the memory and executable
by the processor, and at least one of a user interface, an
operating system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes receiving a first
input from at least one of the user interface, the operating
system, the accelerometer, the gyroscope, the GPS receiver, the
microphone, the magnetometer, the camera, the light sensor, the
temperature sensor, the altitude sensor, the pressure sensor, the
proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device, the first
input originating from one or more identifying events perceptible
to at least one of the user interface, the operating system, the
accelerometer, the gyroscope, the GPS receiver, the microphone, the
magnetometer, the camera, the light sensor, the temperature sensor,
the altitude sensor, the pressure sensor, the proximity sensor, the
NFC device, the compass, and the communications interface of the
first mobile device, analyzing the first input with the
determination module executing at the processor to identify one or
more vehicle determination characteristics within the first input,
and computing at least one determination factor based on the one or
more vehicle determination characteristics. The method further
includes outputting the vehicle class based on the at least one
determination factor.
[0018] According to another aspect, a computer-implemented method
for determining a handheld state of a first mobile device is
provided, the first mobile device having a processor, a memory, a
determination module stored in the memory and executable by the
processor, and at least one of a user interface, an operating
system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes receiving a first
input from at least one of the user interface, the operating
system, the accelerometer, the gyroscope, the GPS receiver, the
microphone, the magnetometer, the camera, the light sensor, the
temperature sensor, the altitude sensor, the pressure sensor, the
proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device, the first
input originating from one or more identifying events perceptible
to at least one of the user interface, the operating system, the
accelerometer, the gyroscope, the GPS receiver, the microphone, the
magnetometer, the camera, the light sensor, the temperature sensor,
the altitude sensor, the pressure sensor, the proximity sensor, the
NFC device, the compass, and the communications interface of the
first mobile device, analyzing the first input with the
determination module executing at the processor to identify one or
more handheld state characteristics within the first input, and
computing at least one determination factor based on the one or
more handheld state characteristics. The method further includes
outputting the handheld state based on the at least one
determination factor.
[0019] According to another aspect, a computer-implemented method
for determining at least one of an in-vehicle role of a user of a
first mobile device, an in-vehicle location or the first mobile
device, a handheld state of the first mobile device, and a vehicle
class of a vehicle containing the first mobile device, using a
central machine is provided, the central machine having a
processor, a memory, and a determination module stored in the
memory and executable by the processor, the central machine further
being communicatively coordinated with the first mobile device, and
the first mobile device having at least one of a user interface, an
operating system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes receiving at least a
first notification from the first mobile device of a first input
from at least one of the user interface, the operating system, the
accelerometer, the gyroscope, the GPS receiver, the microphone, the
magnetometer, the camera, the light sensor, the temperature sensor,
the altitude sensor, the pressure sensor, the proximity sensor, the
NFC device, the compass, and the communications interface of the
first mobile device, the first input originating from an
identifying event perceptible to at least one of the user
interface, the operating system, the accelerometer, the gyroscope,
the GPS receiver, the microphone, the magnetometer, the camera, the
light sensor, the temperature sensor, the altitude sensor, the
pressure sensor, the proximity sensor, the NFC device, the compass,
and the communications interface of the first mobile device,
analyzing at least the first notification with the determination
module executing at the processor to identify at least one of one
or more determination characteristics, one or more handheld state
characteristics and one or more vehicle determination
characteristics within the first notification, and computing at
least one determination factor based on the at least one of the one
or more determination characteristics, the one or more handheld
state characteristics and the one or more vehicle determination
characteristics, the at least one determination factor pertaining
to at least one of (a) the in-vehicle role of the user (b) the
in-vehicle location, (c) the handheld state of the first mobile
device, and (d) a vehicle class. The method further includes at
least one of (a) outputting one or more results, (b) outputting at
least one operation state of the first mobile device, and (c)
adjusting at least one operation state of the first mobile device
at at least one of the central machine and the mobile device, based
on the at least one determination factor.
[0020] According to another aspect, a computer-implemented method
for modifying at least a feature of a first mobile device is
provided, the first mobile device having a processor, a memory, a
determination module stored in the memory and executable by the
processor, and at least one of a user interface, an operating
system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes monitoring at least a
first input provided by at least one of the user interface, the
operating system, the accelerometer, the gyroscope, the GPS
receiver, the microphone, the magnetometer, the camera, the light
sensor, the temperature sensor, the altitude sensor, the pressure
sensor, the proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device, defining an
operation signature based on at least the first input provided by
at least one of the user interface, the operating system, the
accelerometer, the gyroscope, the GPS receiver, the microphone, the
magnetometer, the camera, the light sensor, the temperature sensor,
the altitude sensor, the pressure sensor, the proximity sensor, the
NFC device, the compass, and the communications interface of the
first mobile device, the operation signature reflecting a normal
operation state of the first mobile device, further monitoring at
least a second input provided by at least one of the user
interface, the operating system, the accelerometer, the gyroscope,
the GPS receiver, the microphone, the magnetometer, the camera, the
light sensor, the temperature sensor, the altitude sensor, the
pressure sensor, the proximity sensor, the NFC device, the compass,
and the communications interface of the first mobile device, and
processing at least the second input against the operation
signature to identify a degree of deviation of the second input
from the operation signature or a degree of correlation of the
second input with the operation signature. The method further
includes adjusting at least one operation state of the mobile
device based on the degree of deviation or the degree of
correlation.
[0021] According to another aspect, a computer-implemented method
for restricting operation of a mobile device is provided, the
mobile device having a processor, a memory, a restriction module
stored in the memory and executable by the processor, and at least
one of a user interface, an operating system, an accelerometer, a
gyroscope, a GPS receiver, a microphone, a magnetometer, a camera,
a light sensor, a temperature sensor, an altitude sensor, a
pressure sensor, a proximity sensor, a near-field communication
(NFC) device, a compass, and a communications interface. The method
includes at least one of (i) employing one or more restrictions at
the mobile device, and (ii) employing one or more restrictions in
relation to the mobile device; at least one of the restrictions
dictating at least one operation state of the mobile device,
receiving at least a first input and a second input, each of the
first input and the second input originating at at least one of the
user interface, the operating system, the accelerometer, the
gyroscope, the GPS receiver, the microphone, the magnetometer, the
camera, the light sensor, the temperature sensor, the altitude
sensor, the pressure sensor, the proximity sensor, the NFC device,
the compass, and the communications interface of the mobile device,
and analyzing the first input and the second input to determine a
presence of at least one of (a) two or more users and (b) two or
more mobile devices. The method further modifying an employment of
the at least one restriction includes based on a determination of
the presence of at least one of (a) two or more users; (b) two or
more mobile devices.
[0022] According to another aspect, a computer-implemented method
for restricting operation of a mobile device is provided, the
mobile device having a processor, a memory, a restriction module
stored in the memory and executable by the processor. The method
includes at least one of: (i) employing one or more restrictions at
the mobile device, and (ii) employing one or more restrictions in
relation to the mobile device; at least one of the restrictions
dictating at least one operation state of the mobile device,
wherein at least one restriction is configured to at least one of:
(i) impede operation of the mobile device by a user that is a
driver moreso than the at least one restriction impedes operation
of the mobile device by a user that is a passenger, and (ii) at
least one of (a) impede operation of the mobile device, and (b) be
more likely to be applied to a mobile device used by a driver than
to a mobile device used by a passenger.
[0023] According to another aspect, a computer implemented method
for restricting operation of a first mobile device is provided. The
method includes the steps of: (I) At least one of: (a) determining
that the first mobile device is present within a vehicle and (b)
receiving one or more first inputs from at least one of a vehicle
data system and at least one of a second mobile device, the one or
more first inputs pertaining to a presence of the first mobile
device within a vehicle. The method further includes (II) at least
one of: at least one of: (i) prompting at least one user to provide
one or more stimuli and (ii) receiving one or more second inputs in
response to the prompting; (b) receiving one or more third inputs
from the vehicle data system; and (c) receiving one or more fourth
inputs from at least one of the second mobile device. The method
further includes (III) analyzing at least one of the first inputs,
the second inputs, the third inputs, and the fourth inputs to
determine a presence of at least one of: (a) more than one user,
(b) more than one mobile device, and (c) one or more users not in
the set of users known to be users of the first mobile device. The
method further includes employing one or more restrictions at the
first mobile device (IV) based on a determination of the presence
of at least one of (a) fewer than two users, (b) fewer than two
mobile devices, and (c) fewer than one user not in the set of users
known to be users of the first mobile device.
[0024] According to another aspect, a computer implemented method
for restricting operation of a first mobile device is provided. The
method includes employing at least one restriction at the first
mobile device, receiving one or more inputs from at least one of
(a) the first mobile device; (b) a vehicle data system; and (c) at
least a second mobile device.; and analyzing the one or more inputs
to determine a presence of one or more users that are not known
users of the first mobile device. The method further includes
modifying an employment of the at least one restriction based on a
determination of the presence of one or more users that are not
known users of the first mobile device.
[0025] According to another aspect, a computer-implemented method
for restricting operation of a mobile device using a central
machine is provided, the central machine, having a processor, a
memory, and a restriction module stored in the memory and
executable by the processor, the central machine further being
communicatively coordinated with the mobile device, the mobile
device having at least one of a user interface, an operating
system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes at least one of: (i)
employing one or more restrictions at the mobile device using the
central machine, and (ii) employing one or more restrictions in
relation to the mobile device using the central machine; at least
one of the restrictions dictating at least one operation state of
the mobile device, receiving at least a first input and a second
input from the mobile device, each of the first input and the
second input originating at at least one of the user interface, the
operating system, the accelerometer, the gyroscope, the GPS
receiver, the microphone, the magnetometer, the camera, the light
sensor, the temperature sensor, the altitude sensor, the pressure
sensor, the proximity sensor, the NFC device, the compass, and the
communications interface of the mobile device, and analyzing the
first input and the second input to determine a presence of at
least one of (a) two or more users and(b) two or more mobile
devices. The method further includes based modifying an employment
of the at least one restriction on a determination of the presence
of at least one of (a) two or more users; (b) two or more mobile
devices.
[0026] According to another aspect, a computer-implemented method
for restricting operation of a mobile device using a central
machine is provided, the central machine having a processor, a
memory, a restriction module stored in the memory and executable by
the processor, and the central machine further being
communicatively coordinated with the mobile device. The method
includes at least one of: (i) employing one or more restrictions at
the mobile device using the central machine; and (ii) employing one
or more restrictions in relation to the mobile device using the
central machine, at least one of the restrictions dictating at
least one operation state of the mobile device, wherein at least
one restriction is configured to at least one of: (i) impede
operation of the mobile device by a user that is a driver moreso
than the at least one restriction impedes operation of the mobile
device by a user that is a passenger, and (ii) at least one of (a)
impede operation of the mobile device, and (b) be more likely to be
applied to a mobile device used by a driver than to a mobile device
used by a passenger.
[0027] According to another aspect, a computer-implemented method
for determining an in-vehicle role of a user of a first mobile
device is provided, the first mobile device having a processor, a
memory, a determination module stored in the memory and executable
by the processor, and at least one of a user interface, an
operating system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes receiving a first
input from at least one of the user interface, the operating
system, the accelerometer, the gyroscope, the GPS receiver, the
microphone, the magnetometer, the camera, the light sensor, the
temperature sensor, the altitude sensor, the pressure sensor, the
proximity sensor, the NFC device, the compass, and the
communications interface of the first mobile device, the first
input originating from one or more identifying events perceptible
to at least one of the user interface, the operating system, the
accelerometer, the gyroscope, the GPS receiver, the microphone, the
magnetometer, the camera, the light sensor, the temperature sensor,
the altitude sensor, the pressure sensor, the proximity sensor, the
NFC device, the compass, and the communications interface of the
first mobile device, analyzing the first input with the
determination module executing at the processor to identify one or
more determination characteristics within the first input, and
computing at least one of a probability that the in-vehicle role of
at least the user of the first mobile device is a driver and a
probability that the in-vehicle role of at least the user of the
first mobile device is a passenger based on the one or more
determination characteristics. The method further includes
transforming at least one operation state of the first mobile
device based on the probability.
[0028] According to another aspect, a computer implemented method
for orienting a coordinate system of a mobile device is provided,
the mobile device having at least one of a user interface, an
operating system, an accelerometer, a gyroscope, a GPS receiver, a
microphone, a magnetometer, a camera, a light sensor, a temperature
sensor, an altitude sensor, a pressure sensor, a proximity sensor,
a near-field communication (NFC) device, a compass, and a
communications interface. The method includes receiving at least
one input from (i) at least one of the user interface, the
operating system, the accelerometer, the gyroscope, the GPS
receiver, the microphone, the magnetometer, the camera, the light
sensor, the temperature sensor, the altitude sensor, the pressure
sensor, the proximity sensor, the NFC device, the compass, and the
communications interface of the mobile device; and (ii)a vehicle
data system, computing, based on the one or more inputs, an
orientation of the mobile device relative to a coordinate system of
a vehicle, and based on the orientation, at least one of: (i)
interpreting one or more subsequent inputs of the mobile device in
relation to the coordinate system of the vehicle; and (ii)
transforming the one or more subsequent inputs originating at the
first device into values that are comparable with the coordinate
system of the vehicle.
[0029] These and other aspects, features, and advantages can be
appreciated from the accompanying description of certain
embodiments of the invention and the accompanying drawing
figures.
BRIEF DESCRIPTION OF THE DRAWINGS
[0030] FIG. 1 is a high-level diagram illustrating an exemplary
configuration of an in-vehicle determination system;
[0031] FIGS. 2A-2C are flow diagrams showing routines that
illustrate broad aspects of methods for determining an in-vehicle
role of a user and/or an in-vehicle location of a mobile device in
accordance with various exemplary embodiments disclosed herein;
[0032] FIG. 3 is a flow diagram showing a routing that illustrates
a broad aspect of a method for enabling, disabling and/or modifying
at least a feature of a mobile device in accordance with at least
one exemplary embodiment disclosed herein;
[0033] FIG. 4 is a flow diagram showing a routine that illustrates
a broad aspect of a method for determining an in-vehicle role of a
user of a mobile device and/or a handheld state of a mobile device
and/or a vehicle class of a vehicle containing the first mobile
device using a central machine in accordance with at least one
exemplary embodiment disclosed herein;
[0034] FIG. 5 is a flow diagram showing a routine that illustrates
a broad aspect of a method for determining a vehicle class of a
vehicle using a mobile device in accordance with at least one
exemplary embodiment disclosed herein;
[0035] FIG. 6 is a flow diagram showing a routine that illustrates
a broad aspect of a method of determining a handheld state a mobile
device in accordance with at least one embodiment disclosed
herein;
[0036] FIG. 7 is a flow diagram showing a routine that illustrates
a broad aspect of a method of restricting operation of a mobile
device in accordance with at least one embodiment disclosed
herein;
[0037] FIG. 8 is a flow diagram showing a routine that illustrates
a broad aspect of another method of restricting operation of a
mobile device in accordance with at least one embodiment disclosed
herein;
[0038] FIG. 9A is a diagram depicting an exemplary relative
coordinate system of a mobile device;
[0039] FIG. 9B is a diagram depicting exemplary relative
accelerations and gyroscopic rotations of a mobile device;
[0040] FIG. 9C is a diagram depicting an exemplary gyroscopic sign
convention, as used herein;
[0041] FIG. 10 is a diagram depicting an exemplary coordinate
system used in relation to a vehicle;
[0042] FIGS. 11A-B are diagrams depicting a mobile device and its
respective exemplary coordinate system in various orientations in
relation to a car and its exemplary respective coordinate
system;
[0043] FIG. 12 is a flow diagram showing a routine that illustrates
a broad aspect of another method of restricting operation of a
mobile device in accordance with at least one embodiment disclosed
herein;
[0044] FIG. 13 is a flow diagram showing a routine that illustrates
a broad aspect of another method of restricting operation of a
mobile device in accordance with at least one embodiment disclosed
herein; and
[0045] FIG. 14 is a flow diagram showing a routine that illustrates
a broad aspect of a method for orienting a coordinate system of a
mobile device in accordance with at least one embodiment disclosed
herein.
DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS OF THE INVENTION
[0046] By way of overview and introduction, the present disclosure
details systems and methods for determining various user roles and
actions as they relate to the operation of a mobile device within a
vehicle such as a car. Being that the usage of mobile devices while
driving has been identified as a significant cause of car
accidents, in addition to laws that have been enacted preventing
certain use of mobile phones while driving, various systems and
methods are provided herein which serve to identify the user of a
particular mobile device (for instance, with respect to their role
as a driver or passenger in the car), to identify various aspects
of the usage of the device itself (for instance that the device is
executing a text messaging application), and to identify instances
when a mobile device deviates from its expected or regular
operation.
[0047] As will be described in detail herein, many of these
identifications and/or determinations are made possible through
various sensors, components, and elements that are integrated
within and/or accessible to a mobile device. As is well known to
those of ordinary skill in the art, contemporary smartphones
incorporate a plethora of sensors, including accelerometers, GPS
receivers, and gyroscopes. Various inputs and/or notifications can
be received from these sensors, components, and elements, and can
further be processed in a number of ways in order to arrive at
various conclusions regarding, among others, the user of the mobile
device (such as whether the user is a driver or passenger in a car)
and/or the status of the mobile device itself, and various
probabilities can be ascribed to the conclusions. The operation of
the mobile device can further be adjusted based on such
conclusions, for example, disabling or limiting the operation of a
mobile device upon reaching a likely conclusion that the device is
being operated by a user who is driving a car.
[0048] It will also be appreciated that the systems and methods
disclosed herein can be arranged and/or deployed across a number of
scenarios. In one scenario, the systems and methods can be
principally employed at a mobile device itself, such as in the form
of a mobile application or `app` executing on the mobile device. In
other scenarios, a central machine such as a server in
communication with a mobile device can employ the present systems
and methods. Such a centralized architecture can enable efficient
processing and use of a larger database of user determination
characteristics, eliminates power constraints and enables third
parties, such as law-enforcement agencies and/or insurance
companies, to easily monitor and/or adjust the operation of various
mobile devices.
[0049] The following detailed description is directed to systems
and methods for determining an in-vehicle role of a user of a
mobile device. The referenced systems and methods are now described
more fully with reference to the accompanying drawings, in which
one or more illustrated embodiments and/or arrangements of the
systems and methods are shown. The systems and methods are not
limited in any way to the illustrated embodiments and/or
arrangements as the illustrated embodiments and/or arrangements
described below are merely exemplary of the systems and methods,
which can be embodied in various forms, as appreciated by one
skilled in the art. Therefore, it is to be understood that any
structural and functional details disclosed herein are not to be
interpreted as limiting the systems and methods, but rather are
provided as a representative embodiment and/or arrangement for
teaching one skilled in the art one or more ways to implement the
systems and methods. Accordingly, aspects of the present systems
and methods can take the form of an entirely hardware embodiment,
an entirely software embodiment (including firmware, resident
software, micro-code, etc.) or an embodiment combining software and
hardware. One of skill in the art can appreciate that a software
process can be transformed into an equivalent hardware structure,
and a hardware structure can itself be transformed into an
equivalent software process. Thus, the selection of a hardware
implementation versus a software implementation is one of design
choice and left to the implementer. Furthermore, the terms and
phrases used herein are not intended to be limiting, but rather are
to provide an understandable description of the systems and
methods.
[0050] The terms "determining," "determine," and "determination" as
used herein are intended to encompass the determination,
identification, and/or selection, with any degree of certainty or
precision, and/or any other such operation, function, or action as
it relates to the determination, identification, and/or selection
of a user of a device such as a mobile device, an in-vehicle role
of a user of a device such as a mobile device, a vehicle or vehicle
model/type/class, a device or device model/type/class (e.g.,
handheld or wired), or any other such similar or related operation,
function, or action.
[0051] The terms "identifying event" and "identifying events" as
used herein are intended to encompass one or more occurrences or
instances of events, stimuli, or phenomena, including explicitly
the perceived coordinated or correlated occurrence or instance of
two or more such events, stimuli, and/or phenomena, such as those
originating at one or more devices. It should be understood that
the referenced occurrences or instances of events, stimuli, or
phenomena include single/singular events, stimuli, or phenomena as
well as a set or series of multiple events, stimuli, or phenomena
over a period of time. In addition, the referenced occurrences or
instances of events, stimuli, or phenomena should also be
understood to include one or more coordinations or correlations of
the occurrence or instance of any number of such events, stimuli,
and/or phenomena over any period of time.
[0052] The terms "user interface" and "user interfaces" as used
herein are intended to encompass one or more input devices,
software modules executing in conjunction with one or more
operating systems and/or input devices, or any other such similar
or related device, accessory, apparatus, and/or software
application or module that enable or facilitate input and/or
interaction with a computing device.
[0053] The terms "detect," "detected," "detects," "detecting,"
"detection," and "detections" as used herein are intended to
encompass the detection, measurement, and/or receipt, with any
degree of certainty or precision, one or more occurrences or
instances of events, stimuli, phenomena, or any other such similar
or related inputs that are detectable through one or more devices,
implements or apparatuses.
[0054] The term "processing" as used herein is intended to
encompass comparing, analyzing, weighing, correlating and/or
computing one or more data items, elements, or structures,
individually or in conjunction with one another, using a digital
processor in conjunction with one or more software modules and/or
applications.
[0055] The term "communicatively coordinated" as used herein is
intended to encompass direct or indirect communication between two
or more devices, accessories, and/or apparatuses, expressly
including communications between a first device and a central
machine, wherein the central machine is in turn in communication at
some interval with a second device. In such a scenario, though the
first device and the second device are not, necessarily, in direct
or indirect communication with one another, it can be said that
they are communicatively coordinated with one another by virtue of
their mutual connection to the referenced central machine.
[0056] The terms "feature" and "features" as used herein are
intended to encompass operations, functions, activities, or any
other such similar or related actions, whether automated/automatic
or user-initiated, that occur at or in conjunction with one or more
devices, machines, applications, and/or apparatuses.
[0057] The terms "notification" and "notifications" as used herein
are intended to encompass one or more messages, transmissions,
and/or data packets, such as electronic messages, which contain one
or more data elements (such as inputs) related or relevant to one
or more of the steps, operations, and/or processes disclosed
herein. An illustration of one such notification can be one or more
electronic messages which contain information or data reflecting a
first input from an accelerometer, a gyroscope, and/or a GPS
receiver at a mobile device. Such inputs can be grouped together
into one or more notifications, and these notifications can in turn
be transmitted to and/or received by other devices (such as a
central machine) where they can be further processed.
[0058] The terms "vehicle class" and "vehicle classes" as used
herein are intended to encompass one or more types, categories,
and/or models of vehicle. By way of example, airplanes, trains,
automobiles, motorcycles, and boats can all be said to be different
vehicle classes. By way of further example, sub-categories within a
given vehicle class can also be understood to be different vehicle
classes. Thus, the automobile vehicle class can be further
sub-divided into further vehicle classes such as sedans, vans,
sport utility vehicles (SUVs), and convertibles. These
sub-categories can also be said to be vehicle classes within the
meaning of the term as used herein.
[0059] The terms "operation state" and "operation states" as used
herein are intended to encompass the states of a device, including
any and all operations, functions, capacities, and/or capabilities,
including, explicitly, a set and/or series of any number of
operations, functions, capacities, and/or capabilities, that can be
achieved by and/or in conjunction with a device, such as a mobile
device. Examples of an operation state include, but are not limited
to: an execution of an application (such as an internet browser
application) at a mobile device, a transmission of a notification
(such as sending a text message or email message), a capacity to
receive text messages, and a capability to type text using a
keyboard. Accordingly, the various transformations, adjustments,
and/or modifications disclosed herein that relate to an operation
state and/or operation states should be understood to refer to such
transformations, adjustments, and/or modifications that pertain to
practically any and all operations, functions, capacities, and/or
capabilities that can be achieved by and/or in conjunction with a
device, such as a mobile device.
[0060] The terms "handheld state" and "handheld states" as used
herein are intended to encompass one or more states of a mobile
device with respect to whether or not a user is in direct or
indirect physical contact with the device. For example, the
handheld state of a device in instances where a user holds the
device in his/her hand, carries the device in his/her pocket,
and/or balances the device on his/her knee can all be said to be
"handheld." By way of further example, the handheld state of a
device in instances where the device is positioned in a dock or
cradle, and/or is otherwise not in direct or indirect contact with
a user can be said to be "non-handheld."
[0061] The terms "operational capacity" and "operational
capacities" as used herein are intended to encompass one or more
operation states of a mobile device, particularly with respect to a
central machine such as a server. By way of example, an operational
capacity of a mobile device can be a voice or data connection that
is provided to a mobile device through a central machine, such as
that of a voice/data service provider. Accordingly, it can be
appreciated that a transformation, modification, and/or adjustment
of such an operational capacity preferably entails such a
transformation, modification, and/or adjustment that is initiated
and/or effected by a central machine, preferably in relation to a
mobile device. For example, a central machine can transmit an
instruction and/or notification to a mobile device, such
instruction/notification directing the transformation,
modification, and/or adjustment be implemented at the mobile
device. By way of further example, a central machine can implement
a transformation, modification, and/or adjustment at the central
machine itself, wherein such a transformation, modification, and/or
adjustment--such as the stopping of voice and/or data connections
to a mobile device--ultimately effect the functionality of the
device itself. In both such cases it can be said that the central
machine has transformed, modified, and/or adjusted the operational
capacity of the mobile device.
[0062] The terms "user" and "users" as used herein are intended to
encompass one or more individuals, persons, and/or entities whose
presence a device or machine can preferably be directly or
indirectly aware. It should be understood that while in certain
scenarios a user can interact with a device, in other scenarios a
particular individual, person, and/or entity can be said to be a
"user" within the context of the present disclosure, despite not
interacting with a particular device.
[0063] It should be further understood that while the various
computing devices and machines referenced herein, including but not
limited to the first mobile device, the second mobile device, the
central machine, or any other such similar or related devices or
machines are referred to herein in a as individual/single devices
and/or machines, in certain arrangements the referenced devices and
machines, and their associated and/or accompanying operations,
features, and/or functionalities can be arranged or otherwise
employed across any number of devices and/or machines, such as over
a network connection, as is known to those of skill in the art.
[0064] In addition, it should be understood that while the term
"input" is used herein in the singular form, this is merely for the
sake of clarity and convention. However, the referenced terms
should be understood to encompass both singular inputs as well as a
plurality (two or more) inputs, such as a set of inputs.
[0065] It should be understood that the terms "lateral
acceleration," "x-acceleration," and "x-axis acceleration" as used
herein are used interchangeably, and should thus be understood to
possess the same meaning and connotation. Additionally, the terms
"forward acceleration," "y-acceleration," and "y-axis acceleration"
as used herein are used interchangeably and should thus be
understood to possess the same meaning and connotation. In
addition, the terms "upward acceleration," "z-axis acceleration,"
"z-acceleration" as used herein are used interchangeably and should
thus be understood to possess the same meaning and connotation.
[0066] It should also be understood that the terms "yaw,"
"gyroscopic yaw," "angular velocity around the z-axis," and
"rotation around the z-axis" as used herein are used
interchangeably, and should thus be understood to possess the same
meaning and connotation. In addition, the terms "roll," "gyroscopic
roll," "angular velocity around the y-axis," and "rotation around
the y-axis," as used herein are used interchangeably, and should
thus be understood to possess the same meaning and connotation.
Additionally, the terms "pitch," "gyroscopic pitch," "angular
velocity around the x-axis," and "rotation around the x-axis" as
used herein are used interchangeably, and should thus be understood
to possess the same meaning and connotation.
[0067] An exemplary computer system is shown as a block diagram in
FIG. 1 which is a high-level diagram illustrating an exemplary
configuration of an in-vehicle user-role determination system 100.
In one arrangement, mobile device 105 can be a portable computing
device such as a mobile phone, smartphone, or PDA. In other
arrangements, mobile device 105 can be a tablet computer, a laptop
computer, a personal computer, or an in-vehicle computer (e.g.,
ECU/OBD) though it should be understood that mobile device 105 of
in-vehicle user-role determination system 100 can be practically
any computing device capable of embodying the systems and/or
methods described herein.
[0068] Mobile device 105 of in-vehicle user-role determination
system 100 includes a control circuit 140 which is operatively
connected to various hardware and software components that serve to
enable operation of the in-vehicle user-role determination system
100. The control circuit 140 is operatively connected to a
processor 110 and a memory 120. Processor 110 serves to execute
instructions for software that can be loaded into memory 120.
Processor 110 can be a number of processors, a multi-processor
core, or some other type of processor, depending on the particular
implementation. Further, processor 110 can be implemented using a
number of heterogeneous processor systems in which a main processor
is present with secondary processors on a single chip. As another
illustrative example, processor 110 can be a symmetric
multi-processor system containing multiple processors of the same
type.
[0069] Preferably, memory 120 and/or storage 190 are accessible by
processor 110, thereby enabling processor 110 to receive and
execute instructions stored on memory 120 and/or on storage 190.
Memory 120 can be, for example, a random access memory (RAM) or any
other suitable volatile or non-volatile computer readable storage
medium. In addition, memory 120 can be fixed or removable. Storage
190 can take various forms, depending on the particular
implementation. For example, storage 190 can contain one or more
components or devices. For example, storage 190 can be a hard
drive, a flash memory, a rewritable optical disk, a rewritable
magnetic tape, or some combination of the above. Storage 190 also
can be fixed or removable.
[0070] One or more software modules 130 are encoded in storage 190
and/or in memory 120. The software modules 130 can comprise one or
more software programs or applications having computer program code
or a set of instructions executed in processor 110. Such computer
program code or instructions for carrying out operations for
aspects of the systems and methods disclosed herein can be written
in any combination of one or more programming languages, including
an object oriented programming language such as Java, Smalltalk,
C++ or the like and conventional procedural programming languages,
such as the "C" programming language or similar programming
languages. The program code can execute entirely on the mobile
device 105, partly on mobile device 105, as a stand-alone software
package, partly on mobile device 105 and partly on a remote
computer/device or entirely on the remote computer/device or
server. In the latter scenario, the remote computer can be
connected to mobile device 105 through any type of network,
including a local area network (LAN) or a wide area network (WAN),
or the connection can be made to an external computer (for example,
through the Internet using an Internet Service Provider).
[0071] Software modules 130, including program code/instructions,
are located in a functional form on one or more computer readable
storage devices (such as memory 120 and/or storage 190) that can be
selectively removable. The software modules 130 can be loaded onto
or transferred to mobile 105 for execution by processor 110. It can
also be said that the program code of software modules 130 and one
or more computer readable storage devices (such as memory 120
and/or storage 190) form a computer program product.
[0072] It should be understood that in some illustrative
embodiments, one or more of software modules 130 can be downloaded
over a network to storage 190 from another device or system via
communication interface 150 for use within in-vehicle user-role
determination system 100. For instance, program code stored in a
computer readable storage device in a server can be downloaded over
a network from the server to in-vehicle user-role determination
system 100.
[0073] Preferably, included among the software modules 130 is a
determination module 170 that is executed by processor 110. During
execution of the software modules 130, and specifically the
determination module 170, the processor 110 configures the control
circuit 140 to determine an in-vehicle role of a user of the mobile
device 105, as will be described in greater detail below. It should
be understood that while software modules 130 and/or determination
module 170 can be embodied in any number of computer executable
formats, preferably software modules 130 and/or determination
module 170 comprise one or more applications or `apps` that are
configured to be executed at mobile device 105 and/or in relation
to mobile device 105. In other arrangements, software modules 130
and/or determination module 170 are incorporated and/or integrated
within operating system 176. Furthermore, in certain arrangements,
software modules 130 and/or determination module 170 can be
configured to execute at the request or selection of a user of
mobile device 105 (or any other such user having the ability to
execute a program in relation to mobile device 105, such as a
network administrator), while in other arrangements mobile device
105 can be configured to automatically execute software modules 130
and/or determination module 170, without requiring an affirmative
request to execute. The advantages of such an automatic arrangement
can be appreciated in context of a regulatory scheme that mandates
or recommends that software modules 130 and/or determination module
170 be executed by a mobile device 105 some or all of the time, in
furtherance of a campaign to improve driver safety. It should also
be noted that while FIG. 1 depicts memory 120 oriented on control
circuit 140, in an alternate arrangement, memory 120 can be
operatively connected to the control circuit 140. In addition, it
should be noted that other software modules (such as user interface
172 and operating system 176) and other information and/or data
relevant to the operation of the present systems and methods (such
as database 174) can also be stored on storage 190, as will be
discussed in greater detail below.
[0074] A communication interface 150 is also operatively connected
to control circuit 140. Communication interface 150 can be any
interface that enables communication between the mobile device 105
and external devices, machines and/or elements. Preferably,
communication interface 150 includes, but is not limited to, a
modem, a Network Interface Card (NIC), an integrated network
interface, a radio frequency transmitter/receiver (e.g., Bluetooth,
cellular, NFC), a satellite communication transmitter/receiver, an
infrared port, a USB connection, or any other such interfaces for
connecting mobile device 105 to other computing devices and/or
communication networks such as the Internet. Such connections can
include a wired connection or a wireless connection (e.g. 802.11)
though it should be understood that communication interface 150 can
be practically any interface that enables communication to/from the
control circuit 140.
[0075] At various points during the operation of in-vehicle
user-role determination system 100, mobile device 105 can
communicate with one or more mobile devices 160A-N (collectively
mobile devices 160). The mobile devices 160 transmit and/or receive
data to/from the mobile device 105, thereby preferably enhancing
the operation of the in-vehicle user-role determination system 100,
as will be described in greater detail below. It should be
understood that mobile devices 160 can be in direct communication
with mobile device 105, indirect communication with mobile device
105, and/or can be communicatively coordinated with mobile device
105, as will be described in greater detail below. While mobile
device 160 can be practically any device capable of communication
with mobile machine 105, in the preferred embodiment mobile device
160 is a handheld/portable computer, smartphone, personal digital
assistant (PDA), tablet computer, and/or any portable device that
is capable of transmitting and receiving data to/from mobile device
105. It should also be appreciated that in many arrangements,
mobile device 160 will be substantially identical, from a
structural and functional perspective, to mobile device 105.
[0076] It should be noted that while the FIG. 1 depicts the
in-vehicle user-role determination system 100 with respect to
mobile device 160A and mobile device 160N, it should be understood
that any number of mobile devices 160 can interact with in-vehicle
user-role determination system 100 in the manner described
herein.
[0077] Also preferably connected to and/or in communication with
control circuit 140 are one or more sensors 145A-145M (generically
sensors 145). Generally, sensors 145 are various components,
devices, and/or receivers that are preferably incorporated within
and/or in communication with mobile device 105. Sensors 145
preferably detect one or more stimuli, phenomena, or any other such
inputs, as will be described in greater detail below. Examples of
such sensors 145 include, but are not limited to, an accelerometer
145A, a gyroscope 145B, a GPS receiver 145C, a microphone 145D, a
magnetometer 145E, a camera 145F, a light sensor 145G, a
temperature sensor 145H, an altitude sensor 145I, a pressure sensor
145J, a proximity sensor 145K, a near-field communication (NFC)
device 145L, and a compass 145M. As will be described in greater
detail below, mobile device 105 can preferably receive one or more
inputs from one or more sensors 145 in order to determine an
in-vehicle role of a user of mobile device 105.
[0078] In certain arrangements, one or more external databases
and/or servers 162 are also in communication with mobile device
105. As will be described in greater detail below, database/server
162 is preferably a computing and/or storage device, and/or a
plurality of computing and/or storage devices, that contain(s)
information, such as determination characteristics, that can be
relevant to the determination of an in-vehicle role of a user of
mobile device 105.
[0079] Additionally, in certain arrangements a vehicle data system
164, such as an on board diagnostic (OBD) computer or computing
device (e.g., OBD-I, OBD-II), an engine control unit (ECU), a roll
system, an airbag system, a seat-weight sensor system, a seat-belt
sensor system, and/or an anti-lock braking system (ABS) can also be
in communication with mobile device 105. Vehicle data system 164
preferably provides data and/or information from the vehicle itself
that can also be relevant to various determinations disclosed
herein, such as the determination of an in-vehicle role of a user
of mobile device 105, as will be described in greater detail
below.
[0080] At this juncture it should be noted that in certain
arrangements, such as the one depicted in FIG. 1, mobile devices
160, database/server 162, and/or vehicle data system 164 can be in
periodic or ongoing communication with mobile device 105 thorough a
computer network such as the Internet 166. Although not depicted in
FIG. 1, it should be understood that in certain other arrangements,
mobile devices 160, database/server 162, and/or vehicle data system
164 can be in periodic or ongoing direct communication with mobile
device 105, such as through communications interface 150, thus not
requiring the presence of a network (such as the Internet 166) in
order to initiate and maintain communications.
[0081] In the description that follows, certain embodiments and/or
arrangements are described with reference to acts and symbolic
representations of operations that are performed by one or more
devices, such as the in-vehicle user-role determination system 100
of FIG. 1. As such, it will be understood that such acts and
operations, which are at times referred to as being
computer-executed, include the manipulation by the processor of the
computer of electrical signals representing data in a structured
form. This manipulation transforms the data and/or maintains them
at locations in the memory system of the computer, which
reconfigures and/or otherwise alters the operation of the computer
in a manner understood by those skilled in the art. The data
structures in which data is maintained are physical locations of
the memory that have particular properties defined by the format of
the data. However, while an embodiment is being described in the
foregoing context, it is not meant to provide architectural
limitations to the manner in which different embodiments can be
implemented. The different illustrative embodiments can be
implemented in a system including components in addition to or in
place of those illustrated for the in-vehicle user-role
determination system 100. Other components shown in FIG. 1 can be
varied from the illustrative examples shown. The different
embodiments can be implemented using any hardware device or system
capable of running program code. In another illustrative example,
in-vehicle user-role determination system 100 can take the form of
a hardware unit that has circuits that are manufactured or
configured for a particular use. This type of hardware can perform
operations without needing program code to be loaded into a memory
from a computer readable storage device to be configured to perform
the operations.
[0082] For example, mobile device 105 can take the form of a
circuit system, an application specific integrated circuit (ASIC),
a programmable logic device, or some other suitable type of
hardware configured to perform a number of operations. With a
programmable logic device, the device is configured to perform any
number of operations. The device can be reconfigured at a later
time or can be permanently configured to perform any number of
operations. Examples of programmable logic devices include, for
example, a programmable logic array, programmable array logic, a
field programmable logic array, a field programmable gate array,
and other suitable hardware devices. With this type of
implementation, software modules 130 can be omitted because the
processes for the different embodiments are implemented in a
hardware unit.
[0083] In still another illustrative example, in-vehicle user-role
determination system 100 and/or mobile device 105 can be
implemented using a combination of processors found in computers
and hardware units. Processor 110 can have a number of hardware
units and a number of processors that are configured to execute
software modules 130. In this example, some of the processors can
be implemented in the number of hardware units, while other
processors can be implemented in the number of processors.
[0084] In another example, a bus system can be implemented and can
be comprised of one or more buses, such as a system bus or an
input/output bus. Of course, the bus system may be implemented
using any suitable type of architecture that provides for a
transfer of data between different components or devices attached
to the bus system. Additionally, communications interface 150 can
include one or more devices used to transmit and receive data, such
as a modem or a network adapter.
[0085] Embodiments and/or arrangements can be described in a
general context of computer-executable instructions, such as
program modules, being executed by a computer. Generally, program
modules include routines, programs, objects, components, data
structures, etc., that perform particular tasks or implement
particular abstract data types.
[0086] The operation of the in-vehicle user-role determination
system 100 and the various elements and components described above
will be further appreciated with reference to the method for
determining an in-vehicle role of a user of a mobile device as
described below, in conjunction with FIGS. 2A-2C.
[0087] Turning now to FIG. 2A, a flow diagram is described showing
a routine 201 that illustrates a broad aspect of a method for
determining an in-vehicle role of a user of a mobile device 105 in
accordance with at least one embodiment disclosed herein. It should
be appreciated that several of the logical operations described
herein are implemented (1) as a sequence of computer implemented
acts or program modules running on in-vehicle user-role
determination system 100 and/or (2) as interconnected machine logic
circuits or circuit modules within the in-vehicle user-role
determination system 100. The implementation is a matter of choice
dependent on the requirements of the device (e.g., size, energy,
consumption, performance, etc.). Accordingly, the logical
operations described herein are referred to variously as
operations, structural devices, acts, or modules. Various of these
operations, structural devices, acts and modules can be implemented
in software, in firmware, in special purpose digital logic, and any
combination thereof. It should also be appreciated that more or
fewer operations can be performed than shown in the figures and
described herein. These operations can also be performed in a
different order than those described herein.
[0088] The process begins at step 210 where processor 110 executing
one or more of software modules 130, including, preferably,
determination module 170, receives a first input, such as from one
or more of sensors 145, software modules 130, user interface 172,
operating system 176, and/or communication interface 150.
Preferably, the first input originates from one or more identifying
events that are perceptible to at least one of sensors 145, user
interface 172, operating system 176, and/or communication interface
150. Examples of such an input include, but are not limited to, an
acceleration input that originates from an acceleration event
(e.g., the speeding up or slowing down of a car) that is perceived
by accelerometer 145A, a change in geographic location input that
originates from a location changing event (e.g., the movement from
one place to another) that is perceived by GPS receiver 145C,
and/or one or more instances or user interaction (e.g., typing)
that are detected by user interface 172.
[0089] Then, at step 220, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, analyzes at least the first input, such as to identify one or
more determination characteristics within the first input,
including but not limited to user determination characteristics. As
will be described in greater detail below, user determination
characteristics are one or more aspects originating at and/or
derived from an input that provide insight regarding the in-vehicle
role and/or identity of the user that is exerting control over
and/or otherwise associated with a mobile device, such as mobile
device 105. For example, where the first input (received at step
210) is the typing of one or more letters into user interface 172
(such as to compose a SMS message), determination module 170 can
analyze the typing to identify one or more user determination
characteristics (that is, characteristics that contribute to a
determination of the identity of the particular user that is
associated with mobile device 105, as will be described below). In
this case, determination module 170 can analyze the typing patterns
within the first input (such as the time interval in between the
typing of individual letters in the SMS message, the average time
interval in between the typing of individual letters in the SMS
message, and/or the variability among one or more time intervals
between the typing of individual letters in the SMS message). If
there are substantial time intervals in between the typing of
various letters, and/or if the time intervals in between typed
letters vary widely, these factors can indicate that the user of
mobile device 105 is likely distracted and thus unable to type
consistently. Additional examples of analyzing an input to identify
one or more determination characteristics are provided below in
EXAMPLE 1.
[0090] Upon identifying one or more determination characteristics,
such as user determination characteristics, based on the analysis
of an input, at step 230 the processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, computes one or more determination factors (that is, factors
that reflect and/or suggest one or more determinations that can be
arrived at with respect to one or more of the mobile device, its
location, the user, and/or the vehicle). By way of example, a
probability can be computed, based on the user determination
characteristics, that the in-vehicle role of the user of mobile
device 105 is a driver and/or that the in-vehicle role of the user
of the mobile device 105 is a passenger. That is, in certain
arrangements the user determination characteristics identified at
step 220 can provide varying degrees of certitude as to the
identity or role of a user. So, continuing the example provided
with regard to step 220, while, on the one hand, significant time
intervals between typed letters can indicate that the in-vehicle
role of the user is a driver, on the other hand if the time
intervals in between the various letters are, on average,
consistent and/or substantially similar this can indicate that the
user is not necessarily distracted (due to being a driver), but
rather is a passenger and is simply not adept at typing.
Accordingly, in such a case, in one arrangement the computed
probability for such user determination characteristic(s) is
preferably a lesser degree of certainty that the user is a driver
(and/or a passenger), accounting for the potentially conflicting
indications from the various user determination characteristics. By
way of further example, when the user determination characteristics
indicate that a lesser degree of typing inconsistency and/or
shorter intra-character time intervals exists, processor 110
executing software modules 130 preferably computes a probability
that the in-vehicle role of the user of mobile device 105 is a
passenger. Similarly, when a greater degree of typing inconsistency
and/or longer intra-character time intervals exists, processor 110
executing software modules 130 preferably computes a probability
that the in-vehicle role of the user of mobile device 105 is a
driver (being that the user determination characteristics appear
consistent with the activity of a driver within a vehicle). It
should be appreciated that because ranges exist for a particular
user determination characteristic (such as typing consistency), a
probability of an in-vehicle role is preferably computed,
reflecting a degree of certainty that the user of mobile device is
a driver and/or that the user of mobile device is a passenger.
[0091] Then, at step 240, the processor 110 executing one or more
of software modules 130, including, preferably, determination
module 170, transforms an operation state of the mobile device 105
based on the determination factors (such as the probability
computed at step 230), and/or outputs at least one operation state
based on the at least one determination factor, and/or outputs at
least one in-vehicle role of the user based on at least one
determination factor, and/or outputs at least one in-vehicle
location of the mobile device 105 based on at least one
determination factor, and/or outputs at least one result based on
the at least one determination factor. Various of these operations
will be described in greater detail herein. For example, if the
computed probability indicates that the in-vehicle role of a user
of mobile device 105 is likely to be a driver, processor 110 can
coordinate the disabling of one or more features of the mobile
device 105, such as the disabling of any and/or all features that
enable the entry of text into mobile device 105. In doing so,
existing safety risks can be reduced by preventing a user who has
been determined to be likely to be a driver of a vehicle from using
various regular functions of mobile device 105 that are likely to
distract the user and increase safety risks while driving and/or
are restricted and/or prohibited based on the vehicle's current (or
most recently known) location, as preferably determined in
conjunction with GPS 145C. In other arrangements, one or more other
transformations to the operation state of mobile device can be
similarly applied based on the computed probability. For example,
notifications (such as warning notifications) can be provided at
the mobile device 105, notifications can be transmitted to third
parties (notifying a third party, such as a law enforcement agency,
of the in-vehicle role of the user of mobile device 105 and/or of
the particular operation of the mobile device 105, such as that
typing is being performed upon mobile device 105), instructions can
be provided to third parties (such as a cellular service provider)
to change an operation state of mobile device 105 (such as
temporarily disabling the communication ability of mobile device
105), and/or one or more applications executing or executable on
mobile device 105 can be disabled (such as a text messaging
application). At this juncture, it can be appreciated that the
operations corresponding to transforming step 240 can be customized
and/or configured in relation to various probabilities computed at
step 230. That is, certain transformations of the operation state
of mobile device 105 (for example, notifying law enforcement
authorities) may only be appropriate when there is a high
probability (such as greater than 90%) that the in-vehicle role of
a user of mobile device 105 is a driver (and further that the
driver is interacting with mobile device 105 in an illegal manner
while driving), while other transformations may be appropriate even
for lower degrees of probability (for example, it may be
appropriate to provide a warning notification at mobile device 105
even for a 60% probability that the user is a driver). Yet other
transformations can be employed preemptively, wherein the
transformation is applied even before a prohibited interaction
(e.g., typing into an SMS program) occurs, thereby avoiding
restricted or prohibited interaction with mobile device 105, even
at the first instance. Furthermore, as referenced above, in certain
arrangements the user can configure how (that is, the type of
transformation) and when (that is, the probability threshold that
must be met in order to trigger the transformation) the operation
of mobile device 105 is to be transformed. In other arrangements, a
third party can establish such configurations. For example, a
regulatory agency can dictate that one or more transformations be
employed on some or all mobile devices when a particular
probability threshold that a user of the device is a driver is met.
By way of further example, a car insurance provider can provide
incentives to its customers who utilize one or more transformations
and/or probability thresholds suggested and/or dictated by the
insurance company.
[0092] Turning now to FIG. 2B, a flow diagram is described showing
a routine 202 that illustrates a further aspect of a method for
determining an in-vehicle role of a user of a mobile device 105 in
accordance with at least one embodiment disclosed herein. Though
already noted above, it should be particularly appreciated with
reference to FIG. 2B that more or fewer operations can be performed
than shown in the figures and described herein, and that these
operations can be performed in a different order than those
described herein. Thus, in certain arrangements certain of the
operations of FIG. 2B can be performed while others are not, and
further that in certain arrangements can be performed in a sequence
other than that depicted in FIG. 2B.
[0093] The process begins at step 210 where a first input of a
first device 105 is received, and proceeds to step 220 where the
first input is analyzed. Steps 210 and 220 have already been
described above with reference to FIG. 2A and thus will not be
further elaborated upon here as their operation is substantially
identical to steps 210 and 220 described above.
[0094] Then, at step 221, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, receives a second input from one or more of sensors 145,
software modules 130, user interface 172, operating system 176,
and/or communication interface 150. As described above with
reference to step 210, examples of such an input include, but are
not limited to, an input corresponding to an acceleration perceived
by accelerometer 145A, and/or an input corresponding to a change in
geographic location as perceived by GPS receiver 145C.
[0095] At step 222, the second input is analyzed by processor 110
executing determination module 170, in a manner substantially
similar to that described above with reference to step 220, in
order to identify one or more determination characteristics such as
user determination characteristics within the second input. For
example, where the second input (received at step 221) comprises
one or more accelerations detected by accelerometer 145A,
determination module 170 can analyze the accelerations to identify
one or more user determination characteristics within the second
input. Here, determination module 170 can analyze various patterns
within the second input (such as the time and duration of
acceleration and deceleration). Certain patterns, such as frequent
periods of sustained forward acceleration interspersed with
periodic intervals of rapid and/or brief forward deceleration can
indicate that the user of mobile device 105 is likely traveling in,
if not operating, a car which often follows such an
acceleration/deceleration pattern. As described in detail herein,
by identifying one or more user determination characteristics (such
as identifying that the user of mobile device 105 is likely
traveling in a car, as described above), the context and
significance of one or more other user determination
characteristics can be better evaluated and/or quantified. For
example, the typing patterns of a user determined to be traveling
in a moving car are, on average, of greater significance in
determining whether the user of the device is a driver/passenger.
On the other hand, the typing patterns of a user of a mobile device
105 that has been determined not to be traveling in a moving car
can be understood to be, on average, of lesser significance in
determining whether the user of the device is a
driver/passenger.
[0096] Then, at step 223, the processor 110 executing one or more
of software modules 130, including, preferably, determination
module 170, can compare the determination characteristics such as
user determination characteristics identified within the first
input (such as those identified at step 220) with the determination
characteristics such as user determination characteristics
identified within the second input (such as those identified at
step 222). In doing so, one or more patterns, correlations and/or
relationships can be identified between the user determinations
characteristics of the first input and the user determination
characteristics of the second input. By way of illustration,
referring to the examples discussed above, the typing patterns
identified at step 220 can be compared with the
acceleration/deceleration patterns identified at step 222. In doing
so, patterns, correlations, and/or relationships between the typing
patterns and acceleration/deceleration patterns can be identified.
For example, if time intervals between typed characters and/or
typing inconsistencies increase at the same time as substantial
and/or sudden forward and/or lateral acceleration and/or
deceleration, this can further indicate that the user of a mobile
device 105 is a driver. Being that for a driver to engage in a
maneuver with sudden acceleration and/or deceleration the driver is
expected to have temporarily stopped typing due to the increased
attention a driver must pay to his driving activities, if such
accelerations correlate closely with inconsistent typing speeds
and/or slower typing speed and/or such accelerations are just prior
to typing delays, this can be a strong indication that the user of
mobile device 105 is a driver.
[0097] Additional illustrations of scenarios and/or arrangements
wherein multiple inputs are analyzed, compared, correlated, and/or
processed in order to determine various aspects of the roles of one
or more users of a mobile device 105, are provided throughout the
present disclosure.
[0098] At step 224, the processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, compares determination characteristics such as user
determination characteristics (including, but not limited to, the
user determination characteristics from the first input, as
identified at step 220, and/or the user determination
characteristics from the second input, as identified at step 222)
with stored determination characteristics such as user
determination characteristics, such as those stored at one or more
databases, such as database 174 (that is local to mobile device
105) and/or database/server 162 (that is external to mobile device
105). Stored user determination characteristics can be archived
user determination characteristics that have been retained from
previous user determinations that have been performed, can be
generated based on statistical analyses of previous user
determinations, and/or can be defined or established independent of
any particular previous user determination. In comparing user
determination characteristics (such as those identified at step 220
and/or step 222) with stored user determination characteristics
(such as stored user determination characteristics that have
historically demonstrated a high degree of prediction accuracy in
determining an in-vehicle role of a user), the processor 110 can
more accurately compute the probability that the in-vehicle role of
the user of mobile device 105 is a driver or that the in-vehicle
role of the user of mobile device 105 is a passenger. For instance,
following the example referenced above with regard to typing
inconsistencies, if certain typing patterns have historically been
demonstrated as very reliable in determining the in-vehicle role,
of the user, various identified user determination characteristics
(such as those identified at step 220 and/or step 222) can be
compared to such stored determination characteristics (e.g., highly
predictive typing patterns). If the identified determination
characteristics closely correlate to highly reliable/predictive
stored determination characteristics, the identified determination
characteristics can be similarly considered highly reliable and
this correlation can further enhance the reliability of the
computation of a probability regarding the in-vehicle role of a
particular user. Additional examples and illustrations of such
comparisons are provided below at EXAMPLE 1.
[0099] At step 225, processor 110 executing one or more of software
modules 130, including, preferably, determination module 170,
receives an input from another device, such as one of mobile
devices 160. It should be understood that the input received from
mobile device 160 is preferably from among the various types of
inputs referenced above at steps 210 and 221 (for example, an
acceleration input that originates from an acceleration event that
is perceived by accelerometer 145A, and/or a change in geographic
location input that originates from a location changing event that
is perceived by GPS receiver 145C), and thus will not be described
at length here. However, it should be appreciated that this input
originates at mobile device 160 (that is, a device external to
mobile device 105), and thus the input from mobile device 160 is
preferably received by mobile device 105 through communication
interface 150.
[0100] Then, at step 226, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, processes an input of mobile device 105 against an input of
one or more mobile devices 160. In doing so, one or more
determination characteristics such as user determination
characteristics can be identified within the input of the first
mobile device 105. By way of example, various typing patterns
and/or tendencies (referenced above) of mobile device 160 can be
processed against similar typing patterns/tendencies of mobile
device 105 (or, alternatively, various typing patterns and/or
tendencies of mobile device 105 can be processed against similar
typing patterns/tendencies of mobile device 160). In doing so,
processor 110 can analyze and/or identify the degree to which the
input from mobile device 105 deviates from the input received from
mobile device(s) 160, in a manner similar to the comparison
discussed above at step 224 (except that here the input of mobile
device 105 is being processed against an input received from
another mobile device 160, as opposed to comparing one user
determination characteristic with stored characteristics). Thus,
continuing with the provided example, in a case where the typing
tendencies of mobile device 105 are relatively inconsistent, if,
when processing the typing tendencies received from mobile
device(s) 160 against those of mobile device 105 it is revealed
that the typing across many or all of the devices 105 and 160 is
similarly inconsistent, this can indicate that it there is not
necessarily a high probability that the user of mobile device 105
is a driver, despite the inconsistent typing inputs received at the
device 105 (rather, such inconsistent typing may be the result of
the various devices 105 and 160 traveling along an off-road or
bumpy road, which would make consistent typing difficult, even for
passengers in a vehicle). Additionally, if the typing tendencies of
mobile device 105 are relatively consistent, however when
processing such input(s) against inputs from mobile device(s) 160
it is revealed that the typing tendencies of the user of mobile
device 105 are actually relatively inconsistent, this can indicate
a higher probability that the user of mobile device 105 is a driver
of a vehicle (even though the input from mobile device 105,
in-and-of-itself, may not have generated the same conclusion).
[0101] It should be noted that various limitations and/or filters
can be imposed upon the receiving at step 225 and/or the processing
at step 226, to ensure the most accurate results possible. That is,
while in certain arrangements it can be beneficial to receive
inputs from practically any mobile device 160 that is capable of
communication with mobile device 105, in other arrangements it can
be preferably to limit the number of devices and/or inputs that are
received by mobile device 105 on the basis of one or more factors
to ensure that the inputs being received by mobile device 105 from
such external devices 160 are those that can be expected to be of
greatest relevance. Examples of factors that can be considered in
imposing such limitations and/or filters include proximity to
mobile device 105 and/or similarity/compatibility with mobile
device 105. To illustrate, in processing the typing tendencies of
device 105 against those of another device 160, it can be
preferable to ensure that device 160 is in close proximity to
mobile device 105 (such as through a comparison of the location
coordinates obtained from their respective GPS receivers or by
causing one or more of the mobile devices to emit one or more tones
and/or signals (e.g., an audio tone) that can then be received on
other mobile devices that are in close proximity, as described in
detail in EXAMPLE 2), thereby establishing a high likelihood that
mobile device 105 and mobile device 160 are operating within the
same vehicle (and are thus subjected to substantially identical
conditions). To further illustrate, being that various mobile
devices such as smartphones utilize different user interfaces and
button configurations, it can be advantageous in certain
arrangements to compare inputs from one mobile device 105 with
those of another mobile device 160 that is either identical to or
at least highly compatible with mobile device 105 (such as a device
using the same operating system). Due to differences across various
mobile devices and operating systems, ensuring that mobile device
105 and mobile device(s) 160 are similar (if not identical) ensures
that the inputs received from each can be assumed to be highly
comparable.
[0102] Additional examples of processing inputs from one device
105, 160 against those of one or more other devices to identify one
or more determination characteristics are provided below in EXAMPLE
2.
[0103] In addition, in certain arrangements it is preferable that
the inputs from mobile device 105 and those of mobile device 160
that are to be processed against one another/compared are
substantially synchronized from a chronological standpoint. That
is, it is preferable that each of the various inputs be associated
with a particular time (and that the source of such time be a
central clock, such as a server, which can synchronize the various
devices, though it should be understood that in other arrangements
one or more of devices 105, 160 can broadcast timing data that
enables the calibration of the various devices), thereby enabling
the processing of inputs from mobile device 105 with inputs from
mobile device 160 that correspond to the same point in time. Doing
so ensures that the various inputs being processed/compared are
highly comparable, in that they reflect the operations of the
various devices 105 and 160 in response to the same events (e.g,
accelerating/decelerating over the course of a driver). Additional
examples and illustrations of such further processing operations
are provided below in EXAMPLE 3.
[0104] At step 227, processor 110 executing one or more of software
modules 130, including, preferably, determination module 170,
receives an input from vehicle data system 164, such as an on board
diagnostic (OBD) computer or computing device (e.g., OBD-I, OBD-II,
ECU, roll system, airbag system, and/or an ABS), preferably through
communication interface 150. As noted above, vehicle data system
164 preferably provides data and/or information originating at the
vehicle itself. For example, vehicle data system 164 can provide
one or more inputs that reflect various actions or events, such as
a car's acceleration and/or deceleration, steering, braking, and/or
any other such car-related operations. Such inputs can provide
further insight into determining the in-vehicle role of a user of
mobile device 105, as will be described below.
[0105] Then, at step 228, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, processes an input of mobile device 105 against an input of
vehicle data system 164, in a manner similar to that described
above with respect to step 226. However, here an input of mobile
device 105, such as various typing tendencies (as illustrated
above) is processed against an input from vehicle data system 164
that preferably pertains to an operation of a car (e.g., the car
accelerating, braking, and/or swerving) and which is qualitatively
different than the input of mobile device 105 because vehicle data
system 164 cannot necessarily detect the various stimuli
perceptible to mobile device 105, owing in part to the fact that
mobile device 105 is preferably not fixed relative to the car's
coordinate system. As such, the various inputs (that is, the inputs
from mobile device 105 and those from vehicle data system 164) are
compared and/or synchronized from a chronological standpoint,
substantially in the manner described above with respect to step
226. In doing so, inputs from mobile device 105 can be processed
against inputs from vehicle data system 164 (which, in turn,
originate at the car itself), thereby enabling the association of
various inputs from mobile device 105 with events such as the
accelerating, braking, and/or swerving of the car. Thus, following
the typing tendencies example provided, if certain highly erratic
typing tendencies perceived at mobile device 160, occur just prior
and/or closely correlate to various driving operations (reflected
in the inputs from vehicle data system 164) such as accelerating,
braking, and/or swerving, one or more user determination
characteristics can be identified with regard to the input(s) from
mobile device 105, indicating that there is a high likelihood that
the in-vehicle role of the user of mobile device 105 is a
driver.
[0106] At this juncture, it can be appreciated that although
several sections of the forgoing disclosure have referenced the
processing and/or comparison of various inputs against one another
in context of inputs that are qualitatively comparable (such as at
steps 224 and 226, above, referring to the comparison of typing
tendencies from various sources), in other arrangements various
inputs that are not necessarily qualitatively comparable (or, at
least, do not appear to be qualitatively comparable). For example,
in a manner similar to that described above with respect to step
223, an input of typing tendencies from one source (such as mobile
device 105) can be compared with/analyzed against an input of
accelerations/decelerations originating at mobile device 160. The
respective inputs preferably have a timestamp to enable the
chronological comparison between the inputs, as described in
greater detail above with respect to step 226.
[0107] At step 230, processor 110 executing one or more of software
modules 130, including, preferably, determination module 170,
computes one or more determination factors, such as a probability,
based on the various determination characteristics, that the
in-vehicle role of the user of mobile device 105 is a driver and/or
a probability that the in-vehicle role of the user of the mobile
device 105 is a passenger, substantially in the manner described in
detail above with regard to step 230. Then, at step 240, the
processor 110 executing one or more of software modules 130,
including, preferably, determination module 170, transforms an
operation state of the mobile device 105 and/or outputs at least
one operation state based on the at least one determination factor,
and/or outputs at least one in-vehicle role of the user based on at
least one determination factor, and/or outputs at least one
in-vehicle location of the mobile device 105 based on at least one
determination factor, and/or outputs at least one result based on
the at least one determination factor, as also described in detail
above.
[0108] Turning now to FIG. 2C, a flow diagram is described showing
a routine 203 that illustrates a further aspect of a method for
determining an in-vehicle role of a user of a mobile device 105 in
accordance with at least one embodiment disclosed herein. The
process begins at step 210 where an input is received from mobile
device 105, and proceeds to step 220 where the first input is
analyzed. At step 230, a determination factor such as a probability
is computed, based on the various determination characteristics, as
referenced above. Steps 210, 220, and 230 have already been
described above with reference to FIG. 2A and thus will not be
further elaborated upon here as their operation is substantially
identical to steps 210, 220, and 230 described above.
[0109] Then, at step 250, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, outputs one or more results based on the determination
factor(s) computed at step 230. Such results can include, but are
not limited to, one or more files, notifications, and/or
communications that contain and/or reflect operations of the mobile
device 105, and/or one or more operation states of the first mobile
device 105, and the outputting of such results can be dependent
upon a certain probability threshold, as described in detail
herein. For example, in a scenario where mobile device 105 is
configured to output results (such as that the in-vehicle role of a
user is a driver/passenger) when the probability (that is, the
reliability) of such results are greater than 75%, when mobile
device 105 determines with a probability of 80% that the in-vehicle
role of a user of mobile device 105 is a driver, a corresponding
notification can be outputted reflecting such results. Thus, it can
be appreciated that the referenced results can be output based on
the calculated probability that the user of mobile device 105 is a
driver or that the user of mobile device 105 is a passenger. It
should be understood that the outputting referenced at this step
can be employed in a number of ways depending on the particular
arrangement. For example, in certain arrangements the referenced
results can be transmitted to an external device or third-party,
such as a law enforcement agency, insurance company, and/or other
device 160 (for example, a parent receiving results from a child's
device 105), via communication interface 150. It can be appreciated
that, as referenced above with regard to step 240, the outputting
of such results to a law enforcement agency, insurance company,
and/or another device 160 can ensure that such entities are
notified of the various operations and/or operation states of a
particular mobile device 105, especially when it has been
determined that it is highly probable that device 105 is being
operated by a driver of a car. In another arrangement, such results
can be outputted to mobile device 105 itself in any number of ways,
such as by logging the operations and/or operation state(s) of
mobile device 105 at times/intervals when it has been determined,
for instance, that there is a high probability that the user of
mobile device 105 is a driver. Irrespective of whether the results
are output to a third-party or to the device 105 itself, it should
be appreciated that the outputting of such results can provide
insight regarding the operations of the mobile device 105 at a
particular moment and/or interval, which can be utilized later,
such as in investigating car accidents. For example, if a car
accident occurs, a law-enforcement agency can review such outputted
results to determine whether the driver was engaged in various
distracting activities during and/or near the time of the accident
(e.g., mobile device 105 was being used by driver with 93%
certainty, was being used in a hand-held state with 94% certainty,
and was being used for texting with 100% certainty at least 30
seconds prior to the crash). As such, it can be further appreciated
in certain arrangements the various referenced results can be
outputted across any and/or all degrees of probability, thereby
ensuring a comprehensive log of a user results, reflecting the
various operations and/or operation states throughout the course of
operation of the mobile device 105.
[0110] Turning now to FIG. 3, a flow diagram is described showing a
routine 300 that illustrates an aspect of a method for enabling,
disabling and/or modifying at least a feature of a mobile device
105 in accordance with at least one embodiment disclosed
herein.
[0111] The process begins at step 310 where processor 110 executing
one or more of software modules 130, including, preferably,
determination module 170, monitors one or more inputs from one or
more of sensors 145, software modules 130, user interface 172,
operating system 176, and/or communication interface 150. As
described in detail above with reference to step 210, examples of
such inputs include, but are not limited to, an acceleration input,
a geographic location input, and/or one or more instances or user
interaction (e.g., typing).
[0112] Then, at step 320, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170 defines an operation signature based on the inputs monitored at
step 310. The defined operation signature preferably reflects a
normal operation state and/or a range of normal operation states of
the mobile device 105. That is, based on the various inputs
monitored at mobile device 105, over a defined time interval (for
example, a day, a week, and/or a month) an operation signature or
profile can be defined that reflects one or more values or ranges
of values that have been identified as the normal or regular
operation of the device 105, the normal or regular usage of the
device 105 by a particular user, and/or the normal or regular usage
of device 105 and/or a series or class of such devices by a
particular user and/or a series or range of users. For example,
after monitoring inputs from the accelerometer 145A of mobile
device 105 for a period of time, a range of normal acceleration
inputs of the device 105 can be determined. Similarly, upon
monitoring inputs from the user interface 172 of mobile device 105,
a range of normal typing tendencies (e.g., typing speeds, typing
consistency, etc., as described herein) can be determined. These
various inputs can be used to define an operation signature for the
mobile device 105 that reflects the normal operation and/or
operating range of the device 105. It should be appreciated that
the referenced operation signature is not limited to a single input
or type of input, but rather in certain arrangements can be made up
of signatures of two or more types of inputs. For example, in one
arrangement a normal operation signature can be made up of a range
normal accelerometer inputs together with a range of normal typing
tendencies.
[0113] At step 330, processor 110 executing one or more of software
modules 130, including, preferably, determination module 170,
further monitors one or more second inputs from one or more of
sensors 145, software modules 130, user interface 172, operating
system 176, and/or communication interface 150, substantially in
the manner described above with respect to step 310.
[0114] Then, at step 340, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, processes one or more of the second input(s) (monitored at
step 330) against one or more of the operation signature(s)
(defined at step 320). In doing so, processor 110 executing one or
more of software modules 130, including, preferably, determination
module 170, can identify a degree of deviation and/or a degree of
correlation between the second input(s) and the operation
signature(s). By way of example, various typing patterns and/or
tendencies (referenced above) of mobile device 105 can be processed
against an operation signature reflecting a range of normal typing
tendencies of mobile device 105, as referenced above with respect
to step 320 and described in detail herein. In doing so, processor
110 can analyze and/or identify the degree to which the one or more
second input(s) (monitored at step 330) deviate from the operation
signature of mobile device 105 (defined at step 320). Thus,
continuing with the provided example, even in a case where the
monitored typing tendencies of mobile device 105 are not
necessarily highly inconsistent, from an objective standpoint, upon
processing such inputs against an operation signature (such as an
operation signature reflecting that the typing tendencies of the
user of mobile device 105 are generally highly
consistent/accurate), it can be revealed that the monitored typing
tendencies/inputs actually deviate substantially from the mobile
device's 105 operation signature. In this example, such a deviation
from the operation signature (which reflects the normal and/or
expected operation of mobile device 105) can indicate that the
mobile device 105 is being operated under conditions that distract
the user from interacting normally with the device 105, such as
during driving. Similarly, in an alternative example, in a case
where the monitored typing tendencies of mobile device 105 are
relatively inconsistent, from an objective standpoint, upon
processing such inputs against an operation signature (such as an
operation signature reflecting that the typing tendencies of the
user of mobile device 105 are also generally inconsistent, such as
in the case of a new user who is not adept at typing), it can be
revealed that the monitored typing tendencies/inputs (which
otherwise reflect significantly inconsistent typing tendencies)
actually correlate substantially with the mobile device's 105
operation signature. In such an example, the correlation with the
operation signature (which reflects the normal and/or expected
operation of mobile device 105) can indicate that the mobile device
105 is actually being operated under relatively normal/consistent
conditions, and thus should not be assumed to be operated under
distracting conditions, such as driving, as may have otherwise been
concluded based on the inconsistent typing tendencies alone.
[0115] At this juncture, it should be noted that steps 310 and 320
can be repeated on a periodic and/or constant basis, in order to
further refine the operation signature defined at step 320. That
is, it can be appreciated that in certain scenarios a user's
interaction with mobile device 105 can change and/or improve over
time (such as in the case of a new user whose typing skills
gradually improve with repeated use of device 105), and thus the
operation signature of mobile device 105 should be adjusted,
modified, and/or refined accordingly. It can be appreciated that
this process can be achieved in any number of ways. In one
arrangement, mobile device 105 can be configured to periodically
reset its operation signature (such as every month), such that only
recent operations are accounted for in defining the operation
signature. In other arrangements, further inputs that are monitored
can be factored into and/or averaged with previously monitored
inputs, thereby updating an existing operation signature. In yet
other arrangements, further inputs can be factored into and/or
averaged with previously monitored inputs, and the more recent
inputs can be weighted to place greater emphasis upon them, thereby
updating an existing operation signature while accounting for the
fact that more recent inputs are of greater value in defining an
accurate operation signature of a mobile device 105.
[0116] At step 350, processor 110 executing one or more of software
modules 130, including, preferably, determination module 170,
adjusts one or more operations of mobile device 105. Preferably,
this adjustment corresponds to the degree of deviation and/or the
degree of correlation between one or more monitored inputs (such as
the input monitored at step 330) and one or more operation
signature(s) of mobile device 105 (such as the operation signature
defined at step 320). It should be understood that in certain
arrangements, this adjustment is similar to the transformation of
the operation state of mobile device 105 discussed in detail above
with respect to step 240, and/or the outputting of one or more
results discussed in detail above with respect to step 250. For
example, in certain arrangements, processor 110 can coordinate the
disabling of one or more features of the mobile device 105, such as
the disabling of any and/or all features that enable the entry of
text into mobile device 105, while in other arrangements
notifications (such as warning notifications) can be provided at or
transmitted to mobile device 105. Various other examples of
adjustments to one or more operations of mobile device 105 are
described in greater detail above with reference to steps 240 and
250.
[0117] As also described in detail above with respect to step 240,
it should be noted that various of the adjustments employed at step
350 can be customized and/or configured in relation to various
degrees of correlation and/or deviation identified at step 340.
Thus, it can be appreciated that certain adjustments of the
operation of mobile device 105 (for example, notifying law
enforcement authorities) may only be appropriate when a high degree
of deviation from a normal operation state (that is, from the
operation signature) is identified (and, preferably, further that
such a deviation is indicative of restricted or prohibited activity
on the part of the user of mobile device 105). Other adjustments,
such as providing a notification at mobile device 105, may be
appropriate even for lower degrees of correlation/deviation, as
described in detail above.
[0118] Turning now to FIG. 4, a flow diagram is described showing a
routine 400 that illustrates an aspect of a method of determining
at least one of an in-vehicle role of a user of a first mobile
device and/or a handheld state of the first mobile device and/or a
vehicle class of a vehicle containing the first mobile device using
a central machine in accordance with at least one embodiment
disclosed herein. As will be described in greater detail below,
various of the steps and operations that make up routine 400 share
substantial similarities to those described above in connection
with FIGS. 2A-C and 3. However, it should be understood that while
FIGS. 2A-C and 3 principally concern determinations occurring at
mobile device 105, routine 400 is primarily directed to
determinations performed at central machine 168, as will be
described in greater detail below. It should be further noted that,
as described in greater detail below, while any one of the
particular steps, operations, and/or functions are described
throughout the present disclosure as being performed at and/or upon
a particular machine or device (such as mobile device 105, mobile
device 160, and/or central machine 168), such description should be
understood as being exemplary and/or illustrative and not limiting.
Accordingly, it can be appreciated that any and all steps,
operations, and/or functions described herein with regard to a
particular device and/or machine (such as central machine 168)
should be similarly understood to be similarly capably of
employment at another device and/or machine (such as mobile device
105), substantially in the manner described herein, without
departing from the scope of the present disclosure.
[0119] The process begins at step 410 where processor 4110 of
central machine 168 (depicted in FIG. 1) executing one or more of
software modules 4130, including, preferably, determination module
4170, receives (preferably through communication interface 4150) a
first notification from mobile device 105, the first notification
preferably corresponding to an input originating from one or more
of sensors 145, software modules 130, user interface 172, operating
system 176, and/or communication interface 150 of mobile device
105. As described in detail above with respect to step 210, the
first input originates from one or more identifying events that are
perceptible to at least one of sensors 145, user interface 172,
operating system 176, and/or communication interface 150 of mobile
device 105, such as an acceleration input perceived by
accelerometer 145A, a change in geographic location input perceived
by GPS receiver 145C, and/or one or more instances or user
interaction (e.g., typing) detected by user interface 172. A
notification, such as a computer readable file containing
information that reflects the input itself as well as information
that is pertinent to the input (such as the time, date, and a
unique identifier such as a MAC address of mobile device 105) is
preferably generated by mobile device 105 based on the input, and
is transmitted by communication interface 150 of mobile device 105
to central machine 168, preferably via communications network 166.
As noted above, it should be recognized that while FIG. 1 depicts
central machine 168 communicating with mobile device 105 via
network/Internet 166, it should be understood that in other
arrangements central machine 168 communicates with mobile device
105 directly, such as through a direct Bluetooth pairing and/or
through an ah-hoc wireless network.
[0120] Then, at step 420, processor 4110 of central machine 168
executing one or more of software modules 4130, including,
preferably, determination module 4170, analyzes at least the first
notification to identify one or more determination characteristics,
such as one or more of user determination characteristics and/or
one or more handheld state characteristics and/or one or more
vehicle determination characteristics within the notification. As
described in detail above with respect to step 220, user
determination characteristics are one or more aspects originating
at and/or derived from one or more input(s) and/or notification(s)
that provide insight regarding the in-vehicle role, and/or identity
of the user that is exerting control over and/or otherwise
associated with a mobile device, such as mobile device 105.
Similarly, handheld state characteristics are one or more aspects
originating at and/or derived from one or more input(s) and/or
notification(s) that provide insight regarding the handheld state
of a mobile device, such as mobile device 105, such as whether
mobile device 105 is being operated by a user in a handheld or
non-handheld state (for example, various angles and/or sudden
changes perceived by gyroscope 145B can indicate that mobile device
105 is being operated in a handheld state by a user). It can thus
be appreciated that while the underlying analysis performed at the
present step 420 and at step 220, as described above, are
substantially similar, here the analysis is performed by central
machine 168 based on notifications received from mobile device 105,
while at step 220 the analysis is preferably performed by mobile
device 105 itself. Having this analysis performed at central
machine 168 (as opposed to at mobile device 105, from which the
notification analyzed at this step originates) provides several
advantages in certain scenarios over having the analysis performed
at mobile device 105, as described at step 220. For example, the
analysis performed at the present step can be quite resource
intensive, and shifting this analysis to central machine 168
ensures that the system resources of mobile device 105 remain
relatively free. Additionally, in certain arrangements central
machine 168 can be operated by a law enforcement agency, and, as
such, a centralized approach, such as the one described with
respect to FIG. 4, can provide such an agency with the ability to
monitor and/or adjust the operational capacity of mobile device 105
as necessary, as will be described in greater detail below.
Moreover, in certain scenarios this centralized approach can be
easier to implement with respect to regulatory compliance and
preventing tampering. It is expected that both regulatory
authorities who are interested in implementing a solution such as
that described with reference to FIG. 4 are more likely to succeed
in obtaining compliance from mobile device manufacturers and/or
mobile communications providers when requiring a solution that
primarily only requires, from the standpoint of the mobile device
105, periodic notification transmissions from mobile device 105 to
central machine 168. In addition, such a solution can be more
difficult for users to manipulate, modify, and/or `hack,` given
that the primary analysis is performed by central machine 168, as
opposed to mobile device 105.
[0121] At step 430, processor 4110 of central machine 168 executing
one or more of software modules 4130, including, preferably,
determination module 4170, computes one or more determination
factor(s), such as probabilities, based on the determination
characteristics identified at step 420. It should be understood
that, for instance, based on the particular inputs upon which a
notification (which is analyzed at step 420) is based, various user
determination characteristics and/or handheld state characteristics
are generated. For example, as referenced above, in certain
arrangements user determination characteristics are identified
(such as typing tendencies, as referenced above), while in other
arrangements handheld state characteristics (such as one or more
angles detected by mobile device 105, as referenced above) can be
identified, while in yet other arrangements both user determination
characteristics and handheld state characteristics can be
identified. In any event, at step 430, one or more probabilities
are computed by central machine 168, reflecting a probability that
the in-vehicle role of the user of mobile device 105 is a driver, a
probability that the in-vehicle role of the user of the mobile
device 105 is a passenger, a probability that the handheld state of
the mobile device 105 is handheld, and/or a probability that the
handheld state of the mobile device 105 is non-handheld, all in a
manner substantially similar to that described in detail above with
respect to step 230. It should be understood that, as described in
detail above, in certain arrangements the user determination
characteristics and/or handheld state characteristics identified at
step 420 can provide varying degrees of certitude as to the
identity/role of a user and/or the handheld state of mobile device
105. Accordingly, it should be appreciated that because ranges
exist across the spectrum of a particular user determination and/or
handheld state characteristic (such as typing consistency and/or
device angle), a probability that an in-vehicle role of the user of
mobile device 105 is a driver/passenger and/or a probability that a
handheld state of mobile device 105 is handheld/non-handheld
preferably reflects a degree of certainty across such a probability
spectrum, as described in detail above.
[0122] Then, at step 440, processor 4110 of central machine 168
executing one or more of software modules 4130, including,
preferably, determination module 4170, adjusts an operational
capacity of mobile device 105 based on the one or more
determination factor(s), such as at least one of the probabilities
computed at step 430, substantially in the manner described in
detail above with respect to step 240. However, it should again be
understood that while the description pertaining to step 240 above
relates to adjustments and transformations initiated by mobile
device 105 upon itself, here the adjustments to the operation of
mobile device 105 are initiated by central machine 168. For
example, in certain arrangements central machine 168 can transmit
an operation command, such as a command in the form of one or more
notifications, messages, and/or instructions that reflect various
adjustments that are to be made to the operational capacity of
mobile device 105, and such adjustments can then be applied to
mobile device 105 upon its receipt of the transmitted operation
command(s), and/or their application/execution, effecting similar
and/or identical results as those described in detail above with
respect to step 240 (e.g., providing notifications at mobile device
105, restricting operation of mobile device 105, and/or
transmitting notifications from mobile device 105 to third
parties). In other arrangements, central machine 168 can adjust the
operational capacity of mobile device 105 based primarily and/or
exclusively on adjustments made at and/or by central machine 168
which, in turn, preferably effect or otherwise adjust the
operational capacity of mobile device 105. For instance, in an
arrangement where central machine 168 is controlled by a mobile
communications provider such as a cellular communications provider,
an adjustment can be implemented at central machine 168 whereby one
or more of the services provided by mobile communications provider
to mobile device 105 (such as phone, SMS, and/or data services) can
be interrupted and/or otherwise adjusted or modified, thereby
effecting the operation of mobile device 105 through an adjustment
occurring at central machine 168 based on the probability computed
at step 430. It should be noted that in other arrangements,
substantially similar adjustments can be implemented upon and/or
through one or more service providers that provide one or more
services, whether directly or indirectly, to mobile device 105. By
way of illustration, various voice over IP (VoIP) providers, such
as Skype, enable users to achieve voice communications (akin to
telephone calls) over data connections (such as an internet
connection). By way of further illustrations, the `Viber` app
enables similar SMS capabilities over an internet connection. In
any event, it should be understood that the methods and systems
disclosed herein can be configured such that any necessary
adjustment can be implemented upon and/or through the requisite
service provider (for example, by limiting the calling capabilities
of Skype and/or the SMS capabilities of Viber) substantially in the
manner described in detail above.
[0123] At step 450, processor 4110 of central machine 168 executing
one or more of software modules 4130, including, preferably,
determination module 4170, outputs one or more results and/or
operation states of mobile device 105 based on the one or more
determination factor(s), such as the probability or probabilities
computed at step 430, substantially in the same manner as described
in detail above with respect to step 250. But again, as noted
above, it should be understood that while the description provided
above with respect to step 250 pertains to one or more operations
performed at mobile device 105, step 450 primarily pertains to
operations initiated and/or performed by central machine 168.
Accordingly, it can be appreciated that the one or more operation
state(s) outputted by central machine 168 reflect the operation
state(s) of mobile device 105 (for example, that the device is
being used in a handheld state and/or that the device is being used
by a driver). As noted in detail above with respect to step 250,
the outputting of the operation state(s) can be further based upon
one or more determination factor(s), such as one or more
probabilities computed at step 430, which reflects the likelihood
or degree of certainty that a user of mobile device 105 is a
driver/passenger and/or that mobile device 105 is being used in a
handheld/non-handheld state. As also noted in detail above, in
certain arrangements the operation state of mobile device 105 can
be outputted by central machine 168 to an external device or
third-party, such as a law enforcement agency, insurance company,
and/or other device 160, via communication interface 4150. Such
functionality can be advantageous in jurisdictions where
administrative regulations recommend and/or require that entities
such as mobile communications providers provide information to law
enforcement agencies that reflects the unauthorized usage of mobile
devices such as mobile device 105 while the user of the device is
driving. Similarly, such functionality can be advantageous to
insurance companies when processing an insurance claim. Even in
situations where the user of a mobile device, such as mobile device
105, is uncooperative in providing information to the insurance
company, and/or in situations where the mobile device associated
with an involved party is no longer available or has been
destroyed, central machine 168 (which receives and retains the
various pertinent notifications/inputs provided by the various
devices such as mobile device 105) can output the necessary data,
such as the operation state of mobile device 105, thereby assisting
the insurance company to make necessary decisions regarding the
validity of a particular insurance claim.
[0124] Turning now to FIG. 5, a flow diagram is described showing a
routine 500 that illustrates an aspect of a method of determining a
vehicle class of a vehicle using a first mobile device in
accordance with at least one embodiment disclosed herein. As will
be described in greater detail below, determining the vehicle class
of a particular vehicle can provide further insight and accuracy in
the determination of an in-vehicle role of a user of a mobile
device. In addition, it should be understood that the various steps
and/or operations that make up routine 500 share substantial
similarities to those described above in connection with FIGS. 2A-C
and 3-4.
[0125] The process begins at step 510 where processor 110 executing
one or more of software modules 130, including, preferably,
determination module 170, receives a first input from one or more
of sensors 145, software modules 130, user interface 172, operating
system 176, and/or communication interface 150. Preferably, the
first input originates from one or more identifying events that are
perceptible to at least one of sensors 145, user interface 172,
operating system 176, and/or communication interface 150. Examples
of such an input include, but are not limited to, an acceleration
input that originates from an acceleration event (e.g., the
speeding up or slowing down of a car, train, or airplane, in the X
and/or Y and/or Z axis) that is perceived by accelerometer 145A, a
change in geographic location input that originates from a location
changing event (e.g., the movement from one place to another) that
is perceived by GPS receiver 145C.
[0126] Then, at step 520, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, analyzes at least the first input to identify one or more
vehicle determination characteristics within the first input. As
will be described in greater detail below, vehicle determination
characteristics are one or more aspects originating at and/or
derived from an input that provide insight regarding the vehicle
class within or upon which and/or in relation to mobile device 105
is traveling. For example, in many cases the accelerometer
signature (that is, the pattern reflected in the inputs provided by
one or more accelerometer(s) 145A) differs among vehicle classes.
Thus, for example, a train generally accelerates and decelerates in
the path of its movement (that is, the Y-axis) far less frequently
than other vehicles such as cars. Additionally, the acceleration
and deceleration of a train is generally much more smooth and
gradual than that exhibited by most cars. Accordingly,
determination module 170 can analyze the received input(s) in order
to identify one or more vehicle determination characteristics (such
as the referenced accelerometer signature) within the first input.
Additional examples and illustrations of vehicle determination
characteristics are provided below in EXAMPLE 5.
[0127] At this juncture it should be noted that although the
example provided above pertains to an accelerometer signature,
various signatures (such as accelerometer signatures based on
inputs originating at accelerometer 145A and GPS signatures based
on inputs originating at GPS 145C) based on the various sensors 145
can be similarly determined, substantially in the manner described
above. In addition, it should be noted that various composite
signatures, which correlate inputs originating at two (or more) of
the various sensors 145 (e.g., accelerometer 145A and gyroscope
145B, and/or GPS 145C and microphone 145D) can be similarly
determined, substantially in the manner described above. Moreover,
in certain arrangements the various baseline values corresponding
to the vehicle determination characteristics referenced herein
(such as values for vehicle determination characteristics that
correspond to boats, values for vehicle determination
characteristics that correspond to airplanes, etc.) can be stored
and/or provided at databases 174 and/or 162, thereby enabling the
computation of a probability (based on the vehicle determination
characteristics perceived/determined by mobile device 105) that the
vehicle within which mobile device 105 is traveling corresponds to
a particular vehicle class, as will be described in greater detail
below.
[0128] Upon identifying one or more vehicle determination
characteristics based on the analysis of an input, at step 530
processor 110 executing one or more of software modules 130,
including, preferably, determination module 170, computes at least
one determination factor based on the vehicle determination
characteristic(s), such as a probability that the vehicle
corresponds to a particular vehicle class. That is, in certain
arrangements the vehicle determination characteristics identified
at step 520 can provide varying degrees of certitude as to the
particular class of vehicle that mobile device 105 is traveling
within. As noted above and described in greater detail herein,
given varying administrative regulations regarding the use of
various mobile devices when traveling on various classes of
vehicles (whether such regulations apply only to a driver of the
vehicle, such as in the case of a car, or whether such regulations
apply to all passengers in the vehicle as well, such as in the case
of an airplane), identifying (within a certain degree of certainty)
that a mobile device 105 is traveling within a particular class of
vehicle can be significant in further determining whether a
particular type of usage (if not any usage) of the mobile device
105 is unauthorized or otherwise inadvisable. Accordingly,
continuing the example provided with regard to step 520, in a case
where accelerometer 145A of mobile device 105 provides one or more
inputs that are identified as a vehicle determination
characteristic such as an accelerometer signature (that is,
preferably a pattern of inputs from accelerometer 145A), the
accelerometer signature can be compared with one or more baseline
values stored at database(s) 174, 162 that reflect known and/or
computed vehicle determination characteristics of various vehicles
(e.g., boats, cars, etc.). Thus, by comparing one or more presently
identified vehicle determination characteristic(s) with baseline
values stored at database(s) 174, 162, processor 110 executing one
or more of software modules 130, including, preferably,
determination module 170, can identify which of the various
baseline values (corresponding to various vehicles) the presently
identified vehicle determination characteristic(s) most closely
corresponds to, as well as the degree to which it corresponds.
Based on this correspondence, a probability (preferably reflecting
the degree of the correspondence between the presently identified
vehicle determination characteristic(s) and the baseline values)
can be computed, reflecting a degree of certainty that mobile
device 105 is traveling in a particular class of vehicle.
[0129] Then, at step 550, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, outputs a vehicle class based on the one or more determination
factor(s), such as the probability or probabilities computed at
step 530. For example, if, at step 530, it is computed that it is
90% likely that mobile device 105 is traveling in an airplane, at
step 550 a notification can be provided at mobile device 105
indicating that it has been determined that the device is present
in an airplane. In certain arrangements such a notification can
further include a suggestion/instruction that the user of the
device 105 refrain from further use of the device, in deference to
regulatory guidelines. In other arrangements, the vehicle class of
the device within which mobile device 105 is traveling can be
output to a third-party, such as a law enforcement agency, under
appropriate circumstances. Additionally, as noted in detail above
with respect to step 250, such outputting can, in certain
arrangements, be contingent upon a certain minimum probability
being computed (e.g., a 75% or greater probability that a mobile
device 105 is traveling within an airplane), while in other
arrangements the vehicle class can be outputted across any and/or
all degrees of probability.
[0130] It should also be noted that, in certain arrangements, the
processor 110 executing one or more of software modules 130,
including, preferably, determination module 170, can transform an
operation state of mobile device 105 based in whole or in part on
the determination factor(s), such as the probability computed at
step 530. This operation can be further appreciated when employed
in conjunction with a determination of an in-vehicle role of a user
of mobile device 105, such as that depicted in FIGS. 2A-C and
described in detail above. For example, in certain arrangements,
upon determining (preferably to a certain minimum probability) that
a mobile device 105 is traveling within a certain class of vehicle,
there can be little need to further determine the in-vehicle role
of the user of the device 105 (e.g., if the vehicle is an airplane,
all device usage can be prohibited, irrespective of a particular
user's in-vehicle role). By way of further example, in other
arrangements, a transformation (substantially similar to that
described in detail above with respect to step 240) can be employed
based upon both the computed probability that mobile device 105 is
traveling in a car, together with the computed probability (such as
that described in detail above with respect to step 230) that the
in-vehicle role of a user of mobile device 105 is a driver. In such
a scenario, processor 110 can coordinate various transformations
and/or adjustments to the operation(s) of mobile device 105, as
described in detail above with respect to step 240. As also noted
above, in certain arrangements various of the referenced
transformations can be employed only when either one or both of the
probabilities pertaining to the vehicle class within which mobile
device 105 is traveling and/or the in-vehicle role of the user of
mobile device 105 is a driver meet and/or exceed a certain minimum
threshold.
[0131] Turning now to FIG. 6, a flow diagram is described showing a
routine 600 that illustrates an aspect of a method of determining a
handheld state a mobile device in accordance with at least one
embodiment disclosed herein. As will be described in greater detail
below, various of the steps and operations that make up routine 600
share substantial similarities to those described above in
connection with FIGS. 2A-C, 3, 4, and 5. However, it should be
understood that while at least FIG. 4 principally concerns
determinations occurring at central machine 168, routine 600 is
primarily directed to determinations performed at mobile device
105, as will be described in greater detail below.
[0132] The process begins at step 610 where processor 110 executing
one or more of software modules 130, including, preferably,
determination module 170, receives a first input from one or more
of sensors 145, software modules 130, user interface 172, operating
system 176, and/or communication interface 150. Preferably, the
first input originates from one or more identifying events that are
perceptible to at least one of sensors 145, user interface 172,
operating system 176, and/or communication interface 150. As
described in detail above with respect to step 210, the first input
originates from one or more identifying events that are perceptible
to at least one of sensors 145, user interface 172, operating
system 176, and/or communication interface 150 of mobile device
105, such as an acceleration input perceived by accelerometer 145A
and/or a change in orientation input perceived by gyroscope 145B.
It should be noted that in certain arrangements a series of inputs
(such as a number of acceleration inputs over a certain period of
time) and/or a combination of inputs (such as a number of
acceleration inputs and orientation inputs over a period of time)
are received, such as one or more inputs that reflect the incidence
of shaking or vibration at mobile device 105.
[0133] Then, at step 620, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170, analyzes at least the first input to identify one or more
handheld state characteristics within the notification. As
described in detail above with respect to step 420, handheld state
characteristics are one or more aspects originating at and/or
derived from one or more input(s) that provide insight regarding
the handheld state of a mobile device, such as mobile device 105,
such as whether mobile device 105 is being operated by a user in a
handheld or non-handheld state. For example, various orientations
and/or sudden changes perceived by gyroscope 145B (preferably, in
certain scenarios, in combination with one or more inputs from
various other sensors 145 such as accelerometer 145A, GPS 145C,
and/or magnetometer 145E) can indicate that mobile device 105 is
being operated in a handheld state by a user. By way of further
example, a relatively constant pattern of inputs from accelerometer
145A and/or gyroscope 145B can indicate that mobile device 105 is
positioned in a relatively stable manner, thus indicating that it
is being operated in a non-handheld state.
[0134] At step 630, processor 110 executing one or more of software
modules 130, including, preferably, determination module 170,
computes one or more determination factor(s), based on the handheld
state determination characteristic(s), such as a probability that
that the handheld state of mobile device 105 is handheld, or that
the handheld state of mobile device 105 is non-handheld. By way of
example, based on a series of accelerometer 145A and gyroscope 145B
inputs, the pattern of which indicates ongoing vibration and/or
movement, it can be computed that there is a high probability
(e.g., greater than 90%) that mobile device 105 is being operated
in a handheld state. This is because a user of handheld mobile
device 105--and particularly a driver who is further distracted by
his/her driving responsibilities--is liable to produce far more
vibration/shaking that is perceptible by mobile device 105,
especially as compared to a non-handheld device that is stationed
in a dock, for instance. In any event, at step 630, such
probabilities are computed, reflecting a probability that the
handheld state of the mobile device 105 is handheld, and/or a
probability that the handheld state of the mobile device 105 is
non-handheld, in a manner substantially similar to that described
in detail above with respect to steps 230 and 430. It should be
understood that, as described in detail above, in certain
arrangements the handheld state characteristics identified at step
620 can provide varying degrees of certitude as to the handheld
state of mobile device 105. Accordingly, it should be appreciated
that because ranges exist of a particular handheld state
characteristic (such as device shake patterns), a probability that
a handheld state of mobile device 105 is handheld/non-handheld
preferably reflects a degree of certainty across such a probability
spectrum, as described in detail above.
[0135] At step 650, processor 110 executing one or more of software
modules 130, including, preferably, determination module 170,
outputs one or more handheld states of mobile device 105 based on
the one or more determination factor(s), such as the probability or
probabilities computed at step 630, substantially in the same
manner as described in detail above with respect to steps 250, 450,
and 550. For example, if, at step 630, it is computed that it is
90% likely that mobile device 105 is being operated in a handheld
state, at step 650 a notification can be provided at mobile device
105 indicating that it has been determined that the device is being
so operated. In certain arrangements such a notification can
further include a suggestion/instruction that the user of the
device 105 refrain from further use of the device, in deference to
regulatory guidelines. In other arrangements, the handheld state of
mobile device 105 can be output to a third-party, such as a law
enforcement agency, under appropriate circumstances. Additionally,
as noted in detail above with respect to step 250, such outputting
can, in certain arrangements, be contingent upon a certain minimum
probability being computed (e.g., a 90% or greater probability that
a mobile device 105 is operating in a handheld state), while in
other arrangements the handheld state can be outputted across any
and/or all degrees of probability.
[0136] It should also be noted that, as noted above in detail with
respect to FIG. 5, in certain arrangements, the processor 110
executing one or more of software modules 130, including,
preferably, determination module 170, can transform an operation
state of mobile device 105 based in whole or in part on the one or
more determination factor(s), such as the probability computed at
step 630. This operation can be further appreciated when employed
in conjunction with a determination of an in-vehicle role of a user
of mobile device 105, such as that depicted in FIGS. 2A-C and
described in detail above. For example, in certain arrangements,
upon determining (preferably to a certain minimum probability) that
a mobile device 105 is under the control of a driver of a vehicle
(such as by processing the inputs from accelerometer 145A and
gyroscope 145B of mobile device 105 against those of other mobile
devices 160 within the same vehicle, thereby identifying the driver
of the vehicle, as described in detail herein), it can then be
further determined whether mobile device 105, which has been
determined to be under the control of a driver, is being operated
in a handheld state (generally prohibited in most places) or in a
non-handheld state (generally permitted). Accordingly, in such an
arrangement (where mobile device 105 has been determined to be
under the control of a driver and is being used in a handheld
state), a transformation (substantially similar to that described
in detail above with respect to step 240) can be employed In such a
scenario, processor 110 can coordinate various transformations
and/or adjustments to the operation(s) of mobile device 105, as
described in detail above with respect to step 240. As also noted
above, in certain arrangements various of the referenced
transformations can be employed only when either one or both of the
probabilities pertaining to the user role of the user of mobile
device 105 is a driver and/or the handheld state of mobile device
105 is handheld meet and/or exceed a certain minimum threshold.
[0137] Turning now to FIG. 7, a flow diagram is described showing a
routine 700 that illustrates a broad aspect of a method restricting
operation of a mobile device 105 in accordance with at least one
embodiment disclosed herein. As will be described in greater detail
below, various of the steps and operations that make up routine 700
share substantial similarities to those described above in
connection with FIGS. 2A-C, 3, 4, 5, and 6. It should be noted at
the outset that while the following description of routing 700 will
be directed primarily to operations occurring at mobile device 105,
such description is exemplary and intended for the sake of clarity
and consistency. However, it should be understood that any and/or
all of the steps in routine 700 can be similarly employed at
another device/machine, such as at central machine 168, such as in
the manner described in detail above with respect to FIG. 4.
Furthermore, the same principle should be understood and
appreciated with respect to any and all of the various steps,
operations, and/or functions described throughout the present
disclosure. That is, while any one of the particular steps,
operations, and/or functions are described herein as being
performed at and/or upon a particular machine or device (such as
mobile device 105, mobile device 160, and/or central machine 168),
such description should be understood as being exemplary and/or
illustrative and not limiting. Accordingly, it can be appreciated
that any and all steps, operations, and/or functions described
herein with regard to a particular device and/or machine (such as
mobile device 105) should be similarly understood to be similarly
capably of employment at another device and/or machine (such as
central machine 168), substantially in the manner described herein,
without departing from the scope of the present disclosure.
[0138] At step 701, processor 110 executing one or more of software
modules 130, including, preferably, restriction module 171
determines whether mobile device 105 is present with a vehicle,
such as through one or more of the various determination methods
described in detail herein.
[0139] Upon determining the mobile device 105 is within a vehicle
(such as a car, a truck, a van, a motorcycle and a jeep.), at step
703, processor 110 executing one or more of software modules 130,
including, preferably, restriction module 171 determines whether
the vehicle is in motion, such as through one or more of the
various determination methods described in detail herein.
[0140] At step 705 where processor 110 executing one or more of
software modules 130, including, preferably, restriction module
171, employs a first restriction at mobile device 105 and/or in
relation to mobile device 105. As will be described in greater
detail herein, the first restriction is preferably one or more
instructions that dictate at least one operation state of the
mobile device. Examples of such restrictions include but are not
limited to: instructions that disable a particular feature or
functionality of a mobile device 105 (such as the ability to type
text), instructions that disable multiple features or
functionalities of a mobile device 105 (such as the ability to
launch certain applications and the ability to receive text
messages), and instructions that functionally "lock" mobile device
105 by effectively disabling many or all of the functionalities of
the device. It should be understood that in many arrangements, the
referenced first restriction is preferably a default restriction.
That is, in such arrangements the first restriction is employed by
default, such as upon powering on and/or activating mobile device
105. It should be appreciated that in certain arrangements such
restriction can be employed in relation to mobile device 105, such
as by a central machine 168, such as in the manner disclosed in
detail herein, for example with respect to FIG. 4. By way of
illustration, the referenced restriction can be imposed by a
communications provided (which preferably operates central machine
168) to prevent transmission of one or more communications (e.g.,
SMS messages) to a mobile device 105, until an
identification/determination is made, such as identifying that two
or more users are in a vehicle, such as in the manner disclosed in
detail herein.
[0141] It should be understood that in various arrangements,
including many of those described herein, the various restrictions
employed at mobile device 105 are directed towards configuring
mobile device 105 in such a manner that operation of and/or
interaction with the device is difficult, inconvenient, and/or
impossible (that is, it can be said that operation of mobile device
105 is impeded) for a user who is also simultaneously operating a
vehicle. At the same time, such restrictions are also preferably
configured to create minimal, if any, difficulty and/or
inconvenience when operated by and/or interacted with by a user who
is not simultaneously operating a vehicle. In other words, it can
be said that such restrictions preferably impede operation of the
mobile device by a user who is a driver moreso than they impede
operation of the mobile device by a user who is a passenger. As
such, it should be further understood that in certain arrangements
it can be preferably for mobile device 105 to initially determine
that the device is present within a vehicle (such as through one or
more of the various determination methods described in detail
herein) prior to employing such a first restriction. Accordingly,
it can be further appreciated that the various steps and operations
described herein with reference to FIGS. 7-8 can be further
implemented, in certain arrangements, in conjunction with one or
more of the various other methods and systems described in detail
herein, such as those described with reference to FIGS. 2A-6.
Furthermore, it should be recognized that any one or more of the
various steps, operations, routines, functions, and/or figures
disclosed herein can preferably employed in conjunction within any
one or more of the various steps, operations, routines, functions,
and/or figures disclosed herein. Thus, for example, the various
restrictions described in conjunction with FIG. 7 can be employed
in conjunction with the various determination operations described
above. By way of example, one or more of the referenced
restrictions can be employed before the occurrence of and/or in
response to one or more of the determinations described in detail
herein.
[0142] It should be understood that in various arrangements, at
least one of the one or more restrictions that dictate the at least
one operating state of mobile device 105 are determined based on
inputs originating at at least one of the various sensors 145,
etc., as described in greater detail herein.
[0143] At step 707, mobile device 105 preferably prompts one or
more users to initiate and/or provide one or more stimuli that can
be received as inputs at mobile device 105. By way of example,
mobile device 105 can prompt each of the one or more users in a
vehicle to repeat a particular word or series of words projected by
mobile device 105. It should be understood that in certain
arrangements such a prompt can request for the words to be repeated
sequentially while in other arrangements such a prompt can request
for the words to be repeated simultaneously, while in yet other
arrangements the timing of the repetition is of no consequence. It
should be appreciated that such prompting can request practically
any stimulus that can be received and/or analyzed as an input in
the manner described herein.
[0144] At step 710, processor 110 executing one or more of software
modules 130, including, preferably, restriction module 171 receives
at least a first input and a second input (e.g., the referenced
stimuli), in the manner disclosed in detail herein. As has already
been described in detail herein, each of the first input and the
second input preferably originate at one or more of sensors 145,
software modules 130, user interface 172, operating system 176,
and/or communication interface 150, though it should be understood
that the first input and the second input need not originate from
the same source.
[0145] It should be understood that, as referred to herein, such
inputs are referred to as originating at one or more of sensors
145, software modules 130, user interface 172, operating system
176, and/or communication interface 150 in the sense that such
inputs are initially perceived--from the perspective of mobile
device 105--at such components. However, it should be recognized,
as will be appreciated in connection with the following examples,
that in many arrangements and scenarios such inputs (and/or the
stimuli and/or phenomena that trigger them) can ultimately
originate at sources other than at various components of mobile
device 105. Accordingly, it should be appreciated that within the
context of the discussion of the subject matter encompassed by FIG.
7, various inputs are referred to as originating at a particular
component in the sense that they originate from such a component
with respect to mobile device 105. However, it is acknowledge that
such inputs can, in turn, have ultimate origins beyond mobile
device 105 itself, such as from the voice of a particular user
and/or from an external system or device, as illustrated below.
[0146] For example, a first input corresponding to the audio tones
of the voice of a first user can be received at microphone 145D,
and a second input corresponding to the audio tones of the voice of
a second user can also be received at microphone 145D. It should
also be understood that in certain arrangements, one or more of the
various inputs can be received at and/or originate from a source
external to mobile device 105, such as vehicle data system 164 and
or another mobile device 160. By way of example, vehicle data
system 164 can provide an input to mobile device 105 (preferably
received via communication interface 150) indicating the weight
measured on one or more seats of a vehicle, and/or the usage of
seat belts at one or more seats of a vehicle, etc--which can in
turn, indicate that more than one user is within a vehicle. By way
of further example, a detection of mobile device 160 within a
vehicle (using one or more of the methods described herein) can
also indicate that more than one user is within a vehicle.
[0147] At this juncture, it should be noted that while the first
input and the second input have been described herein as being
discrete inputs, such description is merely exemplary and for the
sake of clarity and illustration. Accordingly, while in certain
arrangements the first input and the second input are separate
inputs in the conventional sense--that is, inputs that originate at
two independent sources, in other arrangements the first input and
the second input are actually aspects found within a single input.
For example, a single audio input (such as an audio recording) that
contains two distinct voices (such as the voices of a first user
and a second user) can be processed (in the manner described
herein) to identify such distinct voices within the single audio
input, which are understood to be a first input and a second input
within the context of the present disclosure.
[0148] Then, at step 720, processor 110 executing one or more of
software modules 130, including, preferably, restriction module
171, analyzes the first input and the second input. In doing so,
the presence of at least one of two or more users and/or two or
more mobile devices can be determined, such as a determination of
the presence of a first user and the presence of a second user,
such as in the manner described in detail herein. By way of
illustration, continuing with the example referenced above at step
710, the first and second inputs (that is, the audio tones of the
voices of the first user and the second user) can be analyzed to
identify an audio signature for each of the respective inputs, in a
manner known to those of ordinary skill in the art, and such audio
signatures can then be compared to determine if they are
substantially similar and/or identical (indicating that both inputs
likely originate from the same source, i.e., the same user) or
substantially dissimilar (indicating that each of the inputs likely
originate from different users). Thus, upon identifying that first
input (here, the voice of the first user) is substantially distinct
from the second input (here, the voice of the second user), it can
be concluded at minimum that the device 105 is in the presence of
(if not in close proximity to) a first user and a second user.
Additional illustrations of such inputs to determine the presence
of at least one of two or more users and/or two or more mobile
devices are presented below at EXAMPLE 4.
[0149] Upon determining that mobile device 105 is in the presence
of at least one of (a) two or more users and/or (b) two or more
mobile devices, such as by determining the presence of at least a
first user and a second user, at step 742 processor 110 executing
one or more of software modules 130, including, preferably,
restriction module 171 modifies an employment of at least one
restriction such as the first restriction. That is, being that a
determination (at step 720) that the device is in the presence of
at least two users necessarily indicates that at least one of such
users is not a driver of a vehicle, this conclusion can preferably
trigger and/or initiate the modification of the first restriction.
In certain arrangements, such modification can include the
employment of a second restriction, strengthening of the first
restriction, and/or the easing of the first restriction. In one
arrangement, such a second restriction can include one or more
instructions that dictate one or more operational states of the
mobile device 105 with respect to one or more of the various
sensors 145 of the device. That is, as noted above, such a
restriction can configure mobile device 105 to operate in a manner
that is relatively difficult/inconvenient for a driver while being
relatively unobtrusive for a passenger. Put differently, it can be
said that such restrictions impeded operation of mobile device 105
by a user who is a driver moreso than the same restrictions impede
operation of a mobile device 105 by a user who is a passenger.
Examples of such restrictions include but are not limited to:
requiring that the device only operate in `landscape` mode (which
generally requires two hands for efficient
interaction/navigation--a demand that is relatively simple for a
passenger to comply with but relatively difficult for a driver, who
needs at least one hand to steer the vehicle, to comply with),
requiring that the device operate only at certain orientations (as
detected by one or more of sensors 145, such as gyroscope 145B,
accelerometer 145A, GPS 145C, and magnetometer 145E) such as a
completely upright orientation which is relatively simple for a
passenger to comply with but which is inconvenient for a driver who
will not find such an orientation as comfortable while driving and
who will generally wish to hold the device at alternate
orientations in order to obscure the device from the view of law
enforcement officials), and that the device not operate in a
manner/pattern that is consistent with that of a driver (such as
the various in-vehicle role determinations described in detail
herein). It should be noted that although such restrictions are
generally effective, on average, in impeding operation of a device
by a driver moreso than a passenger, it is recognized that certain
individual drivers may not find such restrictions particularly
inconvenient, while other passengers may find them highly
inconvenient. Nevertheless, on average, such restrictions impede
the operation of mobile device 105 by drivers moreso that they
impede such operation of mobile device by passengers.
[0150] In the event that the presence of at least one of (a) two or
more users and/or (b) two or more mobile devices, such as the
presence of a first user and a second user, are not determined
and/or one or more users not in the set of users known to be users
of the mobile device, is not determined (at step 720), at step 744
processor 110 executing one or more of software modules 130,
including, preferably, restriction module 171 maintains the
employment of the first restriction.
[0151] Turning now to FIG. 8, a flow diagram is described showing a
routine 800 that illustrates a broad aspect of a method restricting
operation of a mobile device 105 in accordance with at least one
embodiment disclosed herein. As will be described in greater detail
below, various of the steps and operations that make up routine 800
share substantial similarities to those described in detail
herein.
[0152] At step 801, processor 110 executing one or more of software
modules 130, including, preferably, restriction module 171
determines whether mobile device 105 is present with a vehicle,
such as through one or more of the various determination methods
described in detail herein.
[0153] Upon determining that mobile device 105 is within a vehicle
(such as a car, a truck, a van, a motorcycle and a jeep.), at step
803, processor 110 executing one or more of software modules 130,
including, preferably, restriction module 171 determines whether
the vehicle is in motion, such as through one or more of the
various determination methods described in detail herein.
[0154] At step 805, processor 110 executing one or more of software
modules 130, including, preferably, restriction module 171, employs
one or more restrictions at mobile device 105 and/or in relation to
mobile device 105, substantially in the manner described above with
respect to step 705. It should be understood that such
restriction(s) are preferably configured to impede operation of
mobile device 105 by a user that is a driver moreso than the
restriction(s) impede operation of mobile device 105 by a user that
is a passenger, as described in detail herein. Examples of
scenarios where the operations of routine 800 can be implemented
include teenage drivers (wherein a parent/guardian wishes to employ
such restrictions, which make it difficult to operate a mobile
device 105 while driver, at all times) and/or phones that are fixed
in vehicles, such as car phones (wherein it is always desirable to
implement such restrictions). It should be appreciated that in
certain arrangements such restriction can be employed in relation
to mobile device 105, such as by a central machine 168, such as in
the manner disclosed in detail herein, for example with respect to
FIG. 4. By way of illustration, the referenced restriction can be
imposed by a communications provided (which preferably operates
central machine 168) to prevent transmission of one or more
communications (e.g., SMS messages) to a mobile device 105, until
an identification/determination is made, such as identifying that
two or more users are in a vehicle, such as in the manner disclosed
in detail herein.
[0155] It should be further understood that in certain
arrangements, such restriction can be further configured to impede
operation of the mobile device, and/or be more likely to be applied
to a mobile device used by a driver than to a mobile device used by
a passenger. By way of example, consider a scenario where a
particular restriction is employed such that if the `shake`
perceived at mobile device 105 exceeds a certain threshold level,
SMS messages cannot be sent from the device. It can be appreciated
that employment of such a restriction does not impede drivers more
than passengers (being that, once employed, it will impede a driver
and a passenger equally), however such a restriction is more
likely, on average, to be employed for drivers than for passengers
(being that drivers, on average, shake their devices more than
passengers). Further such examples are provided at EXAMPLE 4.
[0156] Turning now to FIG. 12, a flow diagram is described showing
a routine 1200 that illustrates a broad aspect of a method for
restricting operation of a mobile device 105 in accordance with at
least one embodiment disclosed herein. As will be described in
greater detail below, various of the steps and operations that make
up routine 1200 share substantial similarities to those described
in detail herein.
[0157] At step 1201, processor 110 executing one or more of
software modules 130, including, preferably, restriction module 171
determines whether a first mobile device 105 is present within a
vehicle, and/or receives one or more first inputs from at least one
of a vehicle data system 164 and/or at least one of a second mobile
device 160, the one or more first inputs pertaining to a presence
of the first mobile device 105 within a vehicle, such as through
one or more of the various determination methods described in
detail herein.
[0158] Then, at step 1207, mobile device 105 preferably prompts one
or more users to initiate and/or provide one or more stimuli that
can be received as inputs at mobile device 105 and/or receives one
or more second inputs in response to the prompting, and/or receives
one or more third inputs from vehicle data system 164, and/or
receives one or more fourth inputs from at least one of the second
mobile device 160, all in the manner described in detail
herein.
[0159] At step 1220, processor 110 executing one or more of
software modules 130, including, preferably, restriction module
171, analyzes at least one of the first inputs, the second inputs,
the third inputs, and the fourth inputs to determine a presence of
at least one of more than one user, more than one mobile device
105, 160, and/or one or more users not in the set of users known to
be users of the first mobile device, substantially in the manner
described in detail herein.
[0160] At step 1242, processor 110 executing one or more of
software modules 130, including, preferably, restriction module 171
employs one or more restrictions at a mobile device 105,
substantially in the manner described in detail herein.
[0161] Turning now to FIG. 13, a flow diagram is described showing
a routine 1300 that illustrates a broad aspect of a method for
restricting operation of a mobile device 105 in accordance with at
least one embodiment disclosed herein. As will be described in
greater detail below, various of the steps and operations that make
up routine 1300 share substantial similarities to those described
in detail herein.
[0162] At step 1305, processor 110 executing one or more of
software modules 130, including, preferably, restriction module
171, employs one or more restrictions at mobile device 105,
substantially in the manner described above with respect to step
705.
[0163] At step 1310, processor 110 executing one or more of
software modules 130, including, preferably, restriction module 171
receives one or more inputs, preferably from at least one of the
mobile device 105, a vehicle data system 164, and/or one or more
other mobile devices 160, substantially in the manner described
above with respect to step 710.
[0164] At step 1320, processor 110 executing one or more of
software modules 130, including, preferably, restriction module
171, analyzes at least one of the inputs, to determine a presence
of one or more users that are not known users of the first mobile
device 105, substantially in the manner described in detail
herein.
[0165] At step 1342, processor 110 executing one or more of
software modules 130, including, preferably, restriction module
171, modified an employment of one or more restrictions at a mobile
device 105, substantially in the manner described in detail
herein.
[0166] Turning now to FIG. 14, a flow diagram is described showing
a routine 1400 that illustrates a broad aspect of a method for
orienting a coordinate system of a mobile device 105 in accordance
with at least one embodiment disclosed herein. As will be described
in greater detail below, various of the steps and operations that
make up routine 1400 can share substantial similarities to those
described in detail herein. It should be understood that the
various steps of routine 1400 will be appreciated with reference to
EXAMPLE 3 below and FIGS. 9-11B, and their accompanying
descriptions.
[0167] At step 1410, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170 receives one or more inputs, preferably from at least one of
(i) at least one of the user interface, the operating system, the
accelerometer, the gyroscope, the GPS receiver, the microphone, the
magnetometer, the camera, the light sensor, the temperature sensor,
the altitude sensor, the pressure sensor, the proximity sensor, the
NFC device, the compass, and the communications interface of the
mobile device 105 and (ii) a vehicle data system 164, substantially
in the manner described in detail herein.
[0168] At step 1430, processor 110 executing one or more of
software modules 130, including, preferably, determination module
170 computes, based on the one or more inputs, an orientation of
the mobile device 105 relative to a coordinate system of a vehicle,
such as a vehicle within which mobile device 105 is traveling.
[0169] At step 1440 based on the orientation, processor 110
executing one or more of software modules 130, including,
preferably, determination module 170 interprets one or more
subsequent inputs of the mobile device 105 in relation to the
coordinate system of the vehicle and/or transforms the one or more
subsequent inputs originating at the first device into values that
are comparable with the coordinate system of the vehicle. See, for
example, FIGS. 11A-B and EXAMPLE 3, below.
[0170] It should be understood that mobile device 105 is preferably
communicatively coordinated with the vehicle data system, that
vehicle data system is preferably configured (e.g., installed) with
the vehicle (e.g., within the vehicle such as a car) and/or that
mobile device is positioned within the vehicle, as described in
detail herein.
[0171] By way of illustration, consider that based on the x, y and
z accelerometers, the exact orientation of the device 105 can be
determined relative to the ground (e.g, based on the gravitational
force shown on the three accelerometers 145A, as is known to those
of skill in the art based on such disciplines as trigonometry).
When the device is within a moving car with additional forces, the
inputs can be averaged over time and/or inputs from the gyroscope
145B can further assist this computation.
[0172] The orientation of the mobile device 105 can be detected
relative to the car, for example, by using the angle between the
device's magnetic north (e.g, from the 3-axis compass sensor) and
the vehicle's GPS heading (as can be shown on the mobile
device).
[0173] Accordingly, it can be appreciated that in the case of a
moving car there are also additional forces (other than gravity).
These forces can be accounted for, for example, through averaging
over time and/or by using the mobile device's gyroscope 145B, as
described herein and using methods known to those of ordinary skill
in the art.
[0174] In the case that there are movements at the mobile device
105 that are unrelated to the car (say the user moved the device),
these can be accounted for through time averaging and/or using the
gyroscope 145B and or filtering out these higher frequency events,
as described herein and using methods known to those of ordinary
skill in the art.
[0175] By way of further illustration, consider that in a mobile
device on a flat table, the Z-accelerometer shows gravity and the
X-accelerometer and Y-accelerometer show 0.
[0176] If the mobile device is rolled or pitched (so that one side
or one corner of the device remains in contact with the table), the
value read by the z-accelerometer goes down (some of the gravity
that it felt in stage one is handed over to the other
accelerometers)and the X-accelerometer (for roll) and
Y-accelerometer (for pitch) go up. The total sum of squares of the
3-accelerometers is always gravity. So we know the exact
orientation of the device with regard to the ground.
[0177] To orient/align the device 105 with the coordinates of a
car, the device's 105 north (detected, e.g., via its compass
sensor) can be compared with the vehicle's GPS (such as from
vehicle data system 164) heading (as read on the device). For
example, (if the device screen is facing up, i.e., the device is
not upside down) and its compass sensor shows that magnetic north
is due north and the GPS heading sensor shows the vehicle is
travelling due west, then the device is rotated 90 degrees to the
right with regard to the car. Accordingly, the exact orientation of
the device with respect to the coordinates of the car, as disclosed
herein and described in greater detail at EXAMPLE 3 and with regard
to FIGS. 9-11B.
[0178] By way of further illustration, in the case of a 2.5 g
lateral acceleration detected at the mobile device 105, that could
be because the mobile device 105 was in a very tight turn (right or
left) or because there was very strong forward acceleration or
deceleration--or some combination thereof. We cannot know what the
car did (if anything) to cause this 2.5 g acceleration until we
understand the orientation of the device 105 within the car and can
transform the 2.5 g lateral acceleration felt on the phone into the
acceleration in the vehicle's coordinate system, which is achieved
through implementation of routine 1400.
[0179] It should be noted that, for the purpose of the simplicity
of the description and without any loss of generality, in one or
more of the examples below, it will be assumed that the various
mobile device(s) 105, 160 is (are) aligned with the vehicle within
which they are traveling, such as as shown in FIG. 11A. That is,
the coordinate system of a particular mobile device 105, 160 should
be understood to be coincident with the vehicle's coordinate
system, as depicted in FIG. 11A and described in greater detail in
EXAMPLE 3. It should be further recognized that in practice, such
as in various arrangements, such as that shown in FIG. 11B, mobile
device 105, 160 is rotated with respect to the coordinate system of
the vehicle in up to three dimensions. In order to correctly
analyze the various inputs originating at sensors 145 of mobile
device 145 within the context of the coordinate system of the
vehicle, the rotation of the particular mobile device 105, 160
relative to the vehicle is preferably computed and the inputs
originating at sensors 145 of the particular mobile device 105, 160
are preferably transformed into values for the coordinate system of
the vehicle. This may be achieved in various ways, examples of
which are provided below.
[0180] It should also be noted the several of the examples provided
herein are presented from an event-centric perspective for the
purpose of clarity. That is, various of the inputs originating at
sensors 145 of mobile device 105, 160 have been described as
corresponding to various real-world events such as turns, bumps,
and/or stops. Accordingly, it should be appreciated that such
event-centric descriptions are provided herein for the purposes of
illustration and clarity, and are not intended in any way to be
understood as limiting the scope of the present disclosure.
Additionally, is should be appreciated that the various
determinations described herein can also be performed from a
sensor-centric perspective, wherein the various inputs originating
at sensors 145 are considered, irrespective of a particular
real-world event to which they correspond. It should be understood
that the various approaches described herein can be employed in
both even-centric and sensor-centric perspectives.
[0181] It should be understood that the following examples
encompass further arrangements and embodiments of the systems and
methods disclosed herein.
EXAMPLE 1
[0182] There are a number of inputs that can be utilized in various
arrangements in order to identify one or more user determination
characteristics, such as the location of a mobile device 105 and/or
if a mobile device 105 is being operated by the driver or by the
passenger of a car/truck/bus, such as:
[0183] Text Writing--As already noted herein, the text writing
patterns of a driver who is multi-tasking between typing (or
otherwise keystroking) and driving are different than those of a
passenger who can fully focus on their typing (or otherwise
keystroking) and remain relatively undistracted. The average time
between keystrokes is generally greater for a driver than for a
passenger. Also, the variability of time between keystrokes is
generally greater for a driver than for a passenger. The frequency
at which typing errors occur and/or are corrected and/or the
frequency at which suspected errors are made relative to the
quantity of text being typed is generally higher for a driver
relative to a passenger. Additionally, correlations exist between
pauses in texting and driving events that can be detected and/or
perceived by sensors 145 of mobile device 105, as noted in detail
above, that are generally more pronounced for the driver than for
the passenger. Moreover, the precision with which the user types
various keys (particularly in the case of a touchscreen/softphone
keyboard) can be useful in determining whether the in-vehicle role
of a user of mobile device 105 is a driver or a passenger. In
addition, the pressure (and variability thereof) that the user
applies to the various keys can be useful in making such a
determination. By way of illustration, as noted above, a driver is
likely to make relatively fewer mistakes and appears to type faster
and more accurately when his/her car is stopped at a traffic light.
Alternatively, as also noted above, there is likely to be a pause
in texting that corresponds to a sudden stop or swerve, indicative
of the driver having to quickly respond to an emergency action
(e.g., suddenly having to brake to avoid hitting stopped traffic,
or a driver having to swerve back into their lane). Additionally,
patterns can be detected that reveal delays and/or pauses during
the typing of single words, in contrast to "thought-delays"
(wherein the user contemplates his/her next composition) that are
more likely to occur after the completion of a word, phrase or
sentence. In addition, a driver is likely press the keys relatively
less accurately than a passenger. A combination of one or more of
the signatures of the keystroke "cadence," frequency of typing
errors, correlation of the keystroke cadence to vehicle movement
patterns, intra-word typing pauses, keystroke precision and
pressure applied can be used to cumulatively identify one or more
user determination characteristics and thus ultimately determine
whether the user of mobile device 105 is a driver or passenger.
[0184] As also noted above, various arrangements preferably
incorporate identification of one or more of the user determination
characteristics referenced above and herein. In certain
arrangements, each user determination characteristic (e.g. error
proportion, correlation of typing speed to acceleration etc.) can
be considered as a point in a K-dimensional space. Classification
algorithms based on supervised learning, as are well known to those
of ordinary skill in the art, can then be applied to the resulting
K-dimensional signature(s) to determine the probability that the
in-vehicle role of the user of mobile device 105 is a driver or a
passenger.
[0185] Text Reading/Screen Viewing--User determination
characteristic(s) can be identified based on patterns in the
reading of text messages (or any other such text item such as an
email or webpage, or any other such viewing of items on a display
screen, such as during the playing of a video game) on a mobile
device 105, thereby serving to distinguish between a driver and a
passenger. For example, drivers tend to change the orientation of
and/or move (e.g. rotate in his/her palm) mobile device 105 more
frequently when attempting to read a message of a given length (in
order to periodically glance back at the road), whereas a passenger
will read such a message in a comparatively more constant state.
This is especially true during road maneuvers that require more
driver concentration, such as turns and accelerations. This
phenomenon can be observed as a high degree of correlation between
vehicle accelerations and/or gyroscopic rotations as detected by
accelerometer 145A and gyroscope 145B, respectively, of mobile
device 105 and the changes in orientation of the mobile device 160
(unrelated to movements in the vehicle) as measured by one or more
of accelerometer 145A, gyroscope 145B, GPS 145C and magnetometer
145E and, in particular, the presence or absence of a (non-vehicle
related) mobile device movements just prior to vehicle movements.
Preferably, once this correlation reaches or exceeds a certain
threshold, the in-vehicle role of the user of mobile device 105 can
be determined to be a driver and/or once this correlation reaches
or exceeds another certain threshold, the in-vehicle role of the
user of mobile device 105 can be determined to be a passenger.
[0186] Driver-Specific Movements--Various movements and/or forces
can be detected by one or more of sensors 145 of mobile device 105
that can be determined to be unique to a driver. In the
alternative, a lack of perception of such unique forces, such as
"signature" forces at a mobile device 105 can indicate that the
user of such a device is not a driver and is thus a passenger. When
in contact with a device 105 (such as when holding it), a driver
influences the movement of a mobile device 105 through
driver-related actions that include pressing and releasing the
gas/brake/clutch pedals and by moving his/her foot from one pedal
to another over the course of driving. For example, prior to a
period of strong and prolonged acceleration perceived by
accelerometer 145A of mobile device 105 (which is typically due to
acceleration, braking, and/or wheel rotation), there is a smaller,
different acceleration and/or angular movement perceived slightly
(in the 100's of milliseconds) in advance, such as at one or more
of sensors 145, that originates at the driver's body maneuver (such
as the pressing of a gas pedal) that initiates the acceleration of
the vehicle. A driver also causes a mobile device 105 to move by
rotating the steering wheel. Thus, in a case where a mobile device
105 is in contact with a driver turning a steering wheel, various
of sensors 145, such as accelerometers 145A and/or gyroscope 145B
of mobile device 105 can detect certain accelerations and
rotations. Based on a retrospective analysis of such inputs--for
instance, analyzing inputs corresponding to acceleration of a car
with inputs perceived immediately prior--it can be determined
whether the user operating such a mobile device 105 is a driver or
a passenger. If such unique/signature forces are perceived in close
proximity (generally, immediately before) acceleration, etc., it
can be determined that the user is a driver. Conversely, if such
inputs are not detected immediately prior to acceleration, it can
be determined that the user is a passenger (provided that the user
is in physical contact or communication with mobile device
105).
[0187] By way of further illustration, prior to a period of strong
and prolonged lateral acceleration and/or gyroscopic yaw perceived
by accelerometer 145A and gyroscope 145B of mobile device 105 due
to turning, there is a smaller, different acceleration and/or
angular movement perceived slightly (in the 100's of milliseconds)
in advance that originates at the driver's body maneuver that
initiates the turning of the steering wheel and that is unlikely to
be that of a passenger.
[0188] This approach can be also applied to other driver movements
(e.g., looking in the mirrors, turning on the directional signal),
wherein the driver's movements will be detected on mobile device
105 that is in contact with the driver slightly before another
signal is detected (e.g., accelerometer 145A or gyroscope 145B for
looking in mirrors, microphone 145D for turning on directional), on
mobile device 105, whereas these serial relationships will not be
present if mobile device 105 is being operated by a passenger.
[0189] In another approach, the mobile device of a driver will, on
average, display larger movements than that of a passenger
measurable by sensors 145 of mobile device 105 due to the fact that
the driver is likely to be holding the mobile device 105 in only
one hand, whereas a passenger is more likely to be using both hands
to hold a mobile device 105, or is capable of increased focus even
when using only one hand to operate mobile device 105. This can
preferably be done by taking the Fourier transform of a 3D
acceleration function and integrating it (squared, i.e. L2-norms)
over N disjoint frequency intervals, as is well known to those of
ordinary skill in the art. The resulting 3N numbers are preferably
a "signature". The signature corresponding to a driver can be
distinguished from that of a passenger using a classification
algorithm, such as SVM, which has preferably been trained on
sufficiently large pre-classified signature bank, as is also known
to those of ordinary skill in the art.
[0190] GPS--GPS 145C of mobile device 105 can be used, preferably,
in certain arrangements, in conjunction with other sensors, to
identify the in-vehicle position of mobile device 105. In certain
arrangements this is achieved in part based on knowledge of the
lane boundaries of the road on which the vehicle is driving (based
on map data or computation/observation), together with a
determination of mobile device's 105 location, using GPS 145C, to
be on the right or left side of such lane. If mobile device 105 is
in the left part of its current lane, then it can be determined to
be on the left side of the vehicle within which it is traveling,
while if it is in the right part of its current lane, then it is on
the right side of the vehicle. Such in-lane location calculations
can further be averaged over time to increase the accuracy of the
location of the mobile device 105 within its then current lane and,
as a result, the accuracy of the determination of the location of
mobile device 105 inside the vehicle.
[0191] Turns--It is well known that when a moving vehicle turns, it
experiences various physical forces that are different at different
points of the vehicle and which can be continuously measured at
every such point on the vehicle during such turn. Among these are:
(a) The timing and magnitude of the lateral acceleration (from the
turn's centripetal force) and/or changes thereto that occur to a
mobile device 105 as the vehicle in which it is located travels in
a turn and that are measured by accelerometer 145A on mobile device
105, and can be compared to (b) the (contemporaneous, led and/or
lagged) timing and magnitude of the forward accelerations measured
by the accelerometer 145A of such mobile device 105 and/or any
changes thereto and/or to (c) the timing and magnitude of the
upward accelerations (z-axis) as measured by accelerometer 145A of
such mobile device 105 and/or changes thereto. These various
detections can preferably be computed together to determine if
mobile device 105 is on right side or left side of the vehicle. For
example, during a right hand turn, a mobile device 105 on the left
side of a vehicle experiences an instantaneous increase in its
forward acceleration and a decrease in its upward acceleration (as
detected by accelerometer 145A), whereas a mobile device 105 on the
right side of the vehicle experiences an instantaneous decrease in
its forward acceleration and an increase in its upward
acceleration. During a left hand turn, a mobile device 105 on the
left side of a vehicle experiences an instantaneous decrease in its
forward acceleration and an increase in its upward acceleration,
whereas a mobile device 105 on the right side of a vehicle
experiences an instantaneous increase in its forward acceleration
and a decrease in its upward acceleration.
[0192] It is noted that the example above and below are among the
numerous examples in which it is assumed, for the simplicity of
explanation and without loss of generality, that the mobile device
is perfectly aligned with the vehicle.
[0193] In certain arrangements, the lateral (right/left) location
of mobile device 105 within a vehicle can be determined by using a
formula such as:
P = Cov ( A For , .omega. ' ) Var ( .omega. ' ) ##EQU00001##
where P is the lateral position of mobile device 105 in the
vehicle, A.sub.For is the forward acceleration of mobile device 105
and .omega. is the angular velocity around the z-axis (yaw) of
mobile device 105 (which is generally equal to the car's angular
velocity around the z-axis (yaw), if mobile device 105 is still,
relative to the vehicle). In various arrangements, .omega. can be
measured using GPS 145C, accelerometer 145A, gyroscope 145B of
mobile device 105, and/or an inbuilt vehicle wheel rotation sensor
of vehicle data system 164 (as can be transmitted via an OBD-like
protocol). In certain arrangements, transformations can be applied
to certain data items prior to applying them to a formula such as
the one provided above, as described in greater detail below.
[0194] In other arrangements, a similar measure can be used for
upward acceleration (as opposed to and/or in addition to forward
acceleration) to measure the second effect.
[0195] In other arrangements, a similar measure can be used to
compare the gyroscopic roll and/or changes thereto with the upward
acceleration and/to changes thereto. It is also noted that this can
also occur for reasons that are unrelated to turns and such
instances may be useful for the purposes described herein as
well.
[0196] Once the lateral in-car location of mobile device 105 is
determined, if the location is sufficiently to the right of the
middle (e.g., P is greater than some suitably chosen positive
threshold), it can be fairly assumed that mobile device 105 cannot
be in the possession of the driver and thus the in-vehicle role of
the user of mobile device 105 can be determined to be a
passenger.
[0197] It should be understood that the term "turn" as used herein
can refer to a turn or any angle and/or curvature and/or any change
in lateral acceleration and/or gyroscopic yaw, no matter how large
or small and the comparisons described above can be applied
discretely or continuously. It should also be appreciated that such
inputs can be perceived at practically any time and/or interval,
even those that do not necessarily correspond to "turns" as
conventionally understood, and such inputs should be understood to
be within the meaning of the term "turns" as used herein.
[0198] Bumps--The lack of smoothness in the road upon which a
vehicle travels can also be used to determine if mobile device 105
is in the front or rear of the vehicle. The timing and
magnitude/degree of upward acceleration (z-acceleration) detected
by accelerometer 145A of mobile device 105 and/or any changes
thereto can be compared (preferably in an automated fashion), over
time, with leads and/or lags of the device itself, based, among
other things, upon the speed at which the vehicle is travelling (as
determined, for example, from the GPS 145C and/or vehicle data
system 164), to determine if mobile device 105 is in the front or
rear of the vehicle. In most cases changes in upward acceleration
will be sensed twice by accelerometer 145A of mobile device
105--once when the front wheels impart such force to mobile device
105 (e.g., a bump, or a pot-hole) and then again when the rear
wheels impart such force to the mobile device 105. The expected
time difference between the two such instances can be measured
based on the vehicle's speed which is known via the GPS 145C of
mobile device 105 and the vehicle's wheel base, which itself can be
calculated with high accuracy over numerous bumps (e.g., if a
vehicle is travelling at 30 m/sec and the bumps are detected 0.1
seconds apart, it can be concluded that the wheel base is 3
meters). Accordingly, if the first instance of upward acceleration
sensed by accelerometer 145A is larger than the second instance of
upward acceleration sensed, and the time in-between the two
accelerations is consistent with the time it takes the vehicle to
travel a distance equal to its wheelbase (at its current speed),
then mobile device 105 can be determined to be in the front of the
vehicle. If the first instance of upward acceleration sensed is
smaller than the value of the second instance of upward
acceleration then mobile device 105 can be determined to be in the
rear of the vehicle. These comparisons can be accumulated over
several occurrences to further improve accuracy and the results can
be passed though a low-pass filter (e.g., a Kalman filter, as are
well known to those of ordinary skill in the art) to provide a
continuously updated result. It should be understood that the
referenced approach can be further expanded to determine if mobile
device 105 is on the right side or the left side of a vehicle, such
as by analyzing information pertaining to passing over
lane-separating bumps twice during a lane change.
[0199] It should be understood that the term "bump" as used herein
can refer to a change of any size in the upward acceleration,
irrespective of positive or negative change and irrespective of how
large or small and the comparisons and filtering described above
can be applied discretely or continuously at regular or irregular
sampling rates.
[0200] Forward vs. Upward Acceleration/Deceleration--It is well
known that when a moving vehicle accelerates/decelerates, it
experiences various physical forces that are different at different
points of the vehicle and which can be continuously measured at
every such point on the vehicle during such acceleration or
deceleration. Among these items are: (a) The timing and magnitude
of the forward acceleration and/or changes thereto that are
perceived by accelerometer 145A and/or the gyroscopic pitch
(rotation around the x-axis) and/or changes thereto that are
perceived by the gyroscope 145B of mobile device 105 as the vehicle
in which mobile device 105 is located travels and that are measured
by mobile device 105, which can, in turn, be compared to (b) the
(contemporaneous, led and/or lagged) timing and magnitude of the
upward accelerations (z-accelerations) of mobile device 105 and/or
any change thereto to determine if mobile device 105 is in the
front or rear of the vehicle (during positive forward acceleration
(e.g. stepping on the gas), mobile device 105 in the front of the
vehicle experiences an increase in its upward acceleration and
positive pitch, whereas a mobile device 105 in the rear of the
vehicle experiences a decrease in its upward acceleration and
positive pitch, while during negative forward acceleration (e.g.,
braking), mobile device 105 in the front of the vehicle experiences
a decrease in its upward acceleration and negative pitch, whereas
mobile device 105 in the rear of the vehicle experiences an
increase in its upward acceleration and negative pitch).
[0201] In one arrangement, this correlation can be continuously
measured over a constant time window with a formula such as:
corr ( A For , A up ) = cov ( A For , A up ) var ( A For ) var ( A
up ) ##EQU00002##
where A.sub.For is the forward acceleration and A.sub.up is the
upward acceleration.
[0202] In other arrangements, a similar measure can be used to
compare the upward acceleration and/or changes thereto with the
gyroscopic pitch and/or changes thereto (as opposed to and/or in
addition to forward acceleration) to measure this effect.
[0203] Entry & In-Vehicle Movements--The signature of a user
entering a vehicle, as perceived by one or more of sensors 145 of
the user's mobile device 105, is also identifiable. The signatures
for entering a vehicle on the right side are different than those
for entering on the left side (mobile device 105 experiences
lateral acceleration to the left in the former case and to the
right in the latter case--which can be determine using an
integration of the axis-aligned acceleration figures at the
relevant timespan before the car began to move). Similarly, the
signatures of a user entering a rear seat differ from those of a
user entering a front seat. For the United States and most other
countries, a user that enters in the left-front of a vehicle is the
driver, and all other occupants are, by default, passengers. In
arrangements where mobile device 105 is capable of communication
with the vehicle's on-board computer system (e.g., vehicle data
system 164), such communication allows the vehicle to transmit
useful information to mobile device 105 (which can preferably be
received via communication interface 150), such as which vehicle
door was opened and closed thereafter. This allows mobile device
105 to identify its user as a driver. In addition, the in-vehicle
location of mobile device 105 can be continuously tracked after its
entry into a vehicle using one or more of sensors 145 (as such, the
location of mobile device 105 can be tracked even if one of the
occupants passes mobile device 105 to another occupant). Such
tracking is preferably achieved by double integrating the
acceleration figures and gyroscope values as is done in inertial
navigation systems and known to those skilled in the art.
[0204] Magnetic Field--A vehicle's metallic and electrical parts
influence the magnetic field in the vicinity of and inside such
vehicle. A 3-axis magnetometer 145E of mobile device 105 can be
used to detect these influences by measuring such magnetic field(s)
at various times before and during a vehicle's operation (e.g., a
car that has not yet been started will have a different magnetic
signature than one in which the electric systems are operating) and
by comparing them with known magnetic signatures of different
in-vehicle locations in order to determine the in-vehicle location
of mobile device 105. Such signatures can be universal and/or can
depend on additional parameters such as vehicle model, vehicle
location, etc.
[0205] For example, the major metallic component in most vehicles
is the motor and in most vehicles (e.g., cars, buses), and it is
normally situated in the front part of the vehicle, near the
center. The magnetic field sensed by magnetometer 145E of mobile
device 105 can be compared with the magnetic field that is
otherwise present absent the magnetic disturbances--thereby
indicating the direction of the motor. The lateral component of
that direction is preferably the opposite of the left-right in-car
location of mobile device 105.
[0206] User Baseline vs. Population Baseline--As described in
detail above, such as with respect to step 224, in the
identification of many of the user determination characteristics
described above, the values and signatures measured on and/or
computed with and/or in relation to mobile device 105 are compared
to baseline values (which are preferably stored in one or more
databases 174, 162) in order to determine if mobile device 105 is
that of a driver or a passenger. In certain arrangements, such
baseline values can be independent of the user (e.g., the standard
deviation of the time between keystrokes for all people in the
country using a particular model phone), while in other
arrangements such values can be user dependent (e.g., this mobile
device 105 (or this user of this mobile device 105, if such is
available) usually texts at 100 characters per minute, currently he
is texting at the rate of 10 characters per minute--thus the person
holding it is likely driving).
EXAMPLE 2
[0207] As noted above, such as at steps 222 and 223, considering
multiple inputs can increase the accuracy of one or more of the
determinations described herein, such as the determination of an
in-vehicle role of a user of a mobile device 105, 160. This
advantage is further illustrated above at steps 225 and 226,
wherein inputs from multiple devices are considered in order to
compute such determinations. Further illustrations of such
inputs/determinations include, but are not limited to:
[0208] In-Vehicle Location--In the United States and in most other
countries in the world, drivers are the left-front most occupant in
a vehicle, relative to the front end of the vehicle. By identifying
whether a particular mobile device 105, 160 is or is not the
left-front most device within a vehicle, a determination can be
made that such device 105, 160 is or is not being operated by the
driver.
[0209] It should be understood that the referenced in-vehicle
identification/determination is preferably achieved in conjunction
with communication between mobile device 105 and one or more of
mobile devices 160, whether through direct communication or through
network 166. It should also be appreciated that in certain
arrangements such identification(s)/determination(s) can be
performed in a server-side configuration, while in other
arrangements such identification(s)/determination(s) can be
performed in a client-side configuration. In one such server-side
configuration, one or more software modules 130 are preferably
executing at the various mobile devices 105, 160. One or more of
the modules configure the each of the respective devices 105, 160
to transmit its absolute location coordinates (such as those
provided by GPS 145C and/or an inertial navigation system (INS)
and/or its relative location (e.g., 3 meters from WiFi device
#1234) to central machine 168. Central machine 168 can then process
the various locations coordinates and/or relative locations
received from the various devices 105, 160 in order to determine
which of the various devices 105, 160 are sufficiently close to one
another, over a period of time (e.g., 1 minute, 1 hour, etc.),
based on which it can be determined that such devices 105, 160 are
present within the same vehicle. In a client-side configuration,
the mobile devices 105, 160 communicate between one another (such
as through communication interface 150), exchanging absolute
location and/or relative location and determining which other
devices 105, 160 are in within the same vehicle, substantially in
the manner described above with regard to the server-side
configuration. By way of further example, in certain arrangements
one of devices 105, 160 can emit a tone and/or signal (such as an
audio tone), and only those devices 105, 160 that perceive the
emitted tone are determined to be within close proximity of the
device that emitted the tone.
[0210] In both server-side and client-side configurations, upon
determining which mobile devices 105, 160 are within a particular
vehicle, sensor data (that is, data originating at one or more of
sensors 145, such as location coordinates from GPS 145C, or lateral
accelerations during a turn) from the various devices 105, 160 can
be compared with one another to determine a relative in-vehicle
location of one or more of the devices 105, 160. Such relative
location can be subsequently filtered to generate a real-time
driver-passenger determination, providing increasing accuracy in
driver/passenger identification.
[0211] Turns--(a) The timing and magnitude of the lateral
acceleration (from the turn's centripetal force) and/or changes
thereto detected by one or more sensors 145 (e.g., accelerometer
145A and/or gyroscope 145B) of mobile devices 105, 160 located in
the same vehicle as such vehicle travels through a turn can be
compared; to (b) the (contemporaneous, led and/or lagged) timing
and magnitude of forward accelerations of one another and/or change
thereto; and to (d) the (contemporaneous, led and/or lagged) timing
and magnitude of upward accelerations (z-axis) of one another
and/or changes thereto, to generate a more accurate determination
of the relative location of one or more of the devices 105, 160
within the vehicle, in a manner substantially similar to that
described above in EXAMPLE 1.
[0212] By way of illustration, during the execution of a right-hand
turn, the forces experienced by a mobile device 105, 160 located on
the right-side of the car are lower in magnitude than those
experienced at a mobile device 105, 160 located on the left-side.
This comparison can be further recorded and averaged over a certain
time interval to improve the accuracy of the determination.
Additionally, the accelerations experienced during such a turn will
be detected by one or more of the sensors 145 (e.g., accelerometer
145A) of a mobile device 105, 160 located in the front of a vehicle
before they are detected by those of a mobile device 105, 160
located in the rear of such vehicle. This variation can be measured
and compared between such mobile devices 105, 160 to further
determine the relative in-vehicle location of one or more of the
devices 105, 160.
[0213] In addition, the timing and/or magnitude of the forward
acceleration and/or changes thereto that are perceived by various
devices 105, 160 located in the same vehicle as such vehicle
travels and that are detected by such devices (or their respective
sensors 145) can be compared to the (contemporaneous, led and/or
lagged) timing and magnitude of the upward accelerations (z-axis)
of one another and/or change thereto to generate a more accurate
determination of the front/rear location of one or more of the
devices 105, 160 within the vehicle by using substantially the same
techniques described in EXAMPLE 1 above with regard to "Forward vs.
Upward Acceleration/Deceleration."
[0214] By way of illustration, a correlation of the difference
between forward accelerations of two devices can be computed based
on the average of their respective lateral accelerations. In a
manner similar to that described in EXAMPLE 1 with regard to
"turns," such a correlation reflects the relative lateral positions
of the devices in a highly accurate fashion.
[0215] In other arrangements, when (a) the devices' lateral
accelerations and/or changes thereto are compared with their
gyroscopic yaws and/or changes thereto; and/or (b) the devices'
upward acceleration and/or changes thereto are compared with their
gyroscopic rolls and/or changes thereto, the benefit of having
readings from two or more devices can be derived by averaging
results across devices and/or comparing results between devices in
a manner substantially similar to those described in detail
above.
[0216] Bumps--The timing and magnitude of upward acceleration
(z-axis) and/or changes thereto as detected by one or more sensors
145 of a particular mobile device 105, 160 in a vehicle can be
compared to those detected at one or more other mobile devices 105,
160 within the same vehicle, over time, with leads and/or lags,
based, among other things, upon the speed at which the vehicle is
travelling (as can be determined, for instance, based on inputs
from GPS 145C, and/or vehicle data system 164) to generate a more
accurate determination as to whether a particular mobile device
105, 160 is in the front or rear of the vehicle. This is achieved
in part by using techniques substantially similar to those
described in EXAMPLE 1 above with regard to "Bumps." It should also
be noted that such techniques can also be expanded to determine if
a particular mobile device 105, 160 is on the right side or the
left side of said vehicle (e.g., passing over lane-separating bumps
twice during a lane change).
[0217] Driver-Anticipatory Movements--The driver of a vehicle is
generally better able to anticipate the movements of the vehicle
he/she is driving as compared to the passengers because the driver
is the initiator of many of the movements that the vehicle
undergoes, and can thus anticipate the forces that are created as a
result of the vehicle's movement. Such predictive actions can be
detected by one or more of sensors 145 of mobile devices 105, 160
(e.g., accelerometer 145A and/or gyroscope 145B), and can be
further processed to identify whether a particular mobile device
105, 160 is being used by a driver or a passenger. A driver
instinctively tenses and/or flexes certain of his/her muscles to
adjust for the vehicle movements that are about to occur on
average, more adroitly (less sudden with less corrective body
movement) and more quickly than a passenger does. By way of
illustration, a driver anticipates and compensates for the forces
experienced during a turn quicker and more accurately than a
passenger in the vehicle does. Similarly, a driver anticipates and
compensates for the forces experienced during sharp deceleration
(braking) more quickly and more accurately than a passenger. A
driver also anticipates and compensates for the forces of a lane
change more quickly and more accurately than a passenger. By way of
further illustration, the driver can be thought of as a dampening
system which performs better than a corresponding "passenger"
system, due to the driver's higher degree of consciousness,
awareness, and/or anticipation. In one arrangement, one or more of
the listed effects/phenomena can be detected/identified by
processing one or more inputs from one or more sensors 145, such as
by measuring the change in acceleration (i.e. the L2 norm of the
derivative of the acceleration) over the relevant time window. In
this case the acceleration is preferably further band-pass filtered
to focus only on frequencies relevant to this determination, and to
further exclude other driver-acceleration effects (e.g.,
hand-shaking, etc.) as discussed herein.
[0218] Sounds/Signals--The in-vehicle location of a mobile device
105, 160 can also be determined based on the sounds, signals,
and/or transmissions perceived by one or more sensors 145 of a
mobile device 105, 160 (e.g., microphone 145D) in comparison (or,
alternatively, not in comparison) to the sounds perceived at other
mobile devices 105, 160 within the same vehicle. For example, tones
(whether audible or inaudible) perceived at two devices within the
same train can be processed in order to determine which of the
devices is located more towards the front of the train based on one
or more sounds perceived whenever another train passes the subject
train in the opposite direction. The sound of passing train is
first perceived at the device located more towards the front of the
train, and is only later perceived by the device located farther
back within the train. In an alternative arrangement, a similar
approach can be employed at a single device 105, 160, i.e., without
comparing the sounds perceived at one device 105, 160 to those
heard on another within the same vehicle. Multiple microphones
incorporated within and/or configured with a single device 105, 160
and/or multiple additional devices 105, 160 within the same vehicle
can be used to determine the location of one or more of such
devices 105, 160 within the vehicle by measuring the timing and
signature of the sounds perceived at each microphone and processing
them against/comparing them to one another. Accordingly, it can be
appreciated that in certain arrangements, a substantially identical
process can be employed at each of the respective devices
substantially in parallel (such as the measuring of a sound timing
and signature at a respective device's microphone), and the results
of such parallel processes at the respective can then be compared
(such as at one or both of the devices) in order to determine the
position of the devices relative to one another, in the manner
described above.
[0219] By way of illustration, in a scenario where two mobile
devices 105, 160 are present within a vehicle and each device has
two microphones 145D, each sound that is made using each of the
speakers of the respective devices can be perceived at each of the
four microphones (it should be understood that the methods and
systems disclosed herein further enable the generating and/or
projection of such sounds). The time lags between the sound streams
can be processed to determine eight speaker-microphone distances
(each one reflecting the distance between a particular speaker and
a particular microphone). Such distances, along with known
orientations of the devices 105, 160 (based on inputs received from
one or more of the sensors 145, e.g., gyroscope 145B) can be
processed within one or more geometric equations which, once solved
directly, identify a relative position of a given device. Thus, by
way of illustration, if a first device 105, 160 is determined to be
one meter to the front-left of a second device 105, 160, it can be
determined that the first device belongs to be the driver, while
the second device belongs to the passenger.
[0220] Magnetic Field: A vehicle's metallic and electrical parts
influence the magnetic field in the vicinity of and inside such
vehicle. Inputs originating at a 3-axis magnetometer 145E of a
mobile device 105, 160 can be used to detect and determine these
influences by processing such inputs to determine a magnetic field
at various times before and during such vehicle's operation (e.g.,
a car that has not yet been started will have a different magnetic
signature than one in which the electric systems are operating) and
by comparing them with known magnetic signatures of different
in-vehicle locations in order to determine the in-vehicle location
of such device 105, 160. The presence of two or more devices within
a single vehicle can influence each other's magnetic readings in a
way that can be determined based on their comparison. It should be
understood that in certain arrangements, such signatures are
universal while in other arrangements they depend on additional
parameters such as vehicle model, vehicle location, etc. In
addition, comparing the magnetometer 145E inputs from more than one
mobile device 105, 160 located within the same vehicle can enable a
more accurate determination of the in-vehicle location of one or
more of such devices.
EXAMPLE 3
[0221] As noted above, the processing of the various inputs
discussed herein is preferably enhanced by incorporating various
additional processing operations which serve to further enhance the
accuracy of the determinations that are made. Examples of such
further processing operations include, but are not limited to:
[0222] Clock synchronization--As noted above, in arrangements where
inputs originating from multiple devices 105, 160 are processed
together (such as several of those referenced above in EXAMPLE 2),
it is preferable that simultaneous timing measurements originating
at the respective devices 105, 160 are compared as well. In one
arrangement, this can be effectively achieved by synchronizing the
internal clocks of the respective devices 105, 160. By way of
illustration, a relative displacement can be estimated, and this
estimate can be used to process all relevant inputs such that they
are synchronized to the same clock.
[0223] Examples of such synchronization methods include: (A)
processing time inputs from GPS 145C to compute a mean time
displacement between GPS clock and each the clock of each device
105, 160. The difference between those displacements can be
determined to be the displacement between the devices. (B)
Configuring one of the devices 105, 160 to emit a sound and
receiving the sound at a second device (such as at microphone
145D), and further noting the time the respective events occurred
at each device (that is, the time of the emitting of the sound and
the time of the receipt of the sound) and then repeating same
process in reverse. The noted times can then be subtracted from one
another, reflecting the time that it takes to the sound to travel,
and such values will cancel themselves out, leaving twice the
relevant time displacement remaining.
[0224] Orientation Detection--In discussing the processing of
various inputs, such as those of accelerometer 145A and other
sensors 145, it is preferably that various inputs be identified
and/or separated into elements such as "forward acceleration",
"lateral acceleration" and such. These terms are relative to the
car's coordinate system (e.g. "forward" is the direction of car's
movement) while the raw inputs from the various sensors 145 are
relative to the coordinate system of a mobile device 105, 160 (it
should be understood that while the present example is described
with respect to a car, substantially similar approaches can be
applied to other vehicles as well). In order to transition (rotate)
such inputs, the relative orientation of the mobile device 105, 160
within the coordinate system of the car is preferably established.
The following figures depict the various relative coordinates of
mobile device 105, 160, of a car, and of a mobile device 105, 160
within a car:
[0225] FIG. 9A depicts the relative coordinate system of mobile
device 105, as is known to those of ordinary skill in the art and
referenced herein.
[0226] FIG. 9B depicts the relative accelerations and gyroscopic
rotations of a mobile device, as is known to those of ordinary
skill in the art and referenced herein. It should be understood
that although mobile device 105 is not shown in FIG. 9B for the
sake of clarity, the various relative acceleration and rotations
shown in this figure are relative to a mobile device in the same
position as that shown in FIG. 9A.
[0227] FIG. 9C depicts the gyroscopic sign convention used herein,
as is known to those of ordinary skill in the art and reference
herein.
[0228] FIG. 10 depicts the coordinate system used in relation to a
vehicle (such as at vehicle data system 164) as is known to those
of ordinary skill in the art and reference herein.
[0229] FIGS. 11A-B depict mobile device 105 and its respective
coordinate system in relation to a car and its respective
coordinate system. For example, as will be described in greater
detail below, in certain arrangements the respective coordinate
systems can be transitioned, such that it is recognized, for
example, that the +Z coordinate of the car corresponds to the +Y
coordinate of the mobile device 105, and the +Y coordinate of the
can corresponds to the -Z coordinate of the mobile device 105, as
can be appreciated with reference to FIG. 11B.
[0230] Establishing the orientation of a mobile device 105, 160
within the coordinate system of a car can be accomplished in a
number of ways. By way of illustration, in a `static` approach,
wherein it is assumed that the relative orientation of device 105,
160 is constant (e.g., if the device is attached to a cradle or is
in the pocket of unmoving passenger), the mean acceleration vector
can be determined and be identified as the "down" axis. The
"forward" axis can be determined by comparing/processing inputs
from GPS 145C that correspond to direction angles with inputs from
magnetometer 145E that reflect `north.` The third axis can be
computed based on the first two determined axes using vector
multiplication as is known to those of ordinary skill in the art.
By way of further example, inputs from the accelerometer 145A, the
magnetometer 145E and the GPS 145C (e.g., heading data) can be
averaged, substantially in the manner described above.
[0231] In a dynamic arrangement, inputs originating at
accelerometer 145A, gyroscope 145B and/or other sensors 145 can be
processed to identify real-time changes in the orientation of a
device 105, 160. In addition, acceleration/magnetic/GPS figures can
be generated, preferably using "sensor fusion" algorithms, as is
known to those of ordinary skill in the art. In doing so, the
above-referenced "static" approach can be utilized to dynamically
determine the relative orientation of the device 105, 160.
[0232] It should be noted that the gyroscopic sign convention
adopted herein is preferably such that if an observer positioned on
the positive part of the axis of rotation sees the rotation as
counterclockwise, it is deemed to be positive.
[0233] Low-Pass filtering--The values derived and/or computed from
the various inputs originating at the various sensors 145 of mobile
device 105, 160 can be frequently compromised by the vibration(s)
present in car's environment (originating at the car's engine, road
bumps, imperfect wheels, wind blowing through the windows, or even
car audio sounds). Such vibrations can inject "noise" into the
inputs originating at the various sensors 145, and can adversely
affect the precision of the processing of the various algorithms
disclosed here, both in terms of efficiency and final accuracy.
[0234] There are various ways that this problem can be addressed.
In one arrangement, one or more of devices 105, 160 within the
vehicle are attached to a dampening device. In certain arrangements
such a dampening device can include one or more weight(s) that can
be attached to the mobile device 105, 160 to effectively increase
its mass and thus make it more vibration resistant. Additionally,
dampening materials (e.g. sorbothane pads) can be attached to a
device 105, 160 to prevent high frequency vibrations from passing
to the mobile device 105, 160. In any event, the inputs can be
preferably processed with a bounded pass filter. On such example is
an FIR with 128 taps with Hamming windows.
[0235] Sensor Fusion--As has already been noted and illustrated
above, various determinations can be made by processing inputs from
several sensors 145 together (e.g. forward velocity inputs
originating at both the accelerometer 145A and GPS 145C).
EXAMPLE 4
[0236] The following scenarios illustrate additional examples of
the analyzing of a first and second input and identifying the
presence of a first user and a second user (such as at step 720,
above): Using one or more biometric authentication methods (as are
known to those of ordinary skill in the art) to identify the
presence of a first user and a second user. Such biometric
authentication methods include, but are not limited to, voice
recognition, fingerprint recognition, face recognition, DNA
identification, and retina identification.
[0237] The following are further examples of restrictions that can
be employed at a mobile device 105, such as in the manner described
in detail above with reference to FIG. 7. Various of these examples
impede operation of mobile device 105 by a driver moreso than they
impede operation of the device by a passenger: [0238] (a) If
talking, the device is restricted to being held on the left side
(right side for U.K.) of the head/face of the user and with an
upright orientation, so that driver usage cannot be hidden from
external observers. [0239] (b) If texting, mailing, browsing etc.,
mobile device 105 is restricted to operating when having straight
orientation (no yaw) (adjustment can be necessary, in certain
arrangements, for a vertical/horizontal keyboard) and at least
close to upright orientation (cannot be on knee or low down so that
driver cannot "hide" the device use from external observers).
[0240] (c) The device interface will only function horizontally
(more difficult for driver to use). [0241] (d) The device 105 is
restricted to operating in one or more ways only when camera 145F
perceives a frequently moving background (e.g., be held high, not
hidden low in the driver's lap or blocked by the steering wheel).
[0242] (e) The device 105 is restricted to operating in one or more
ways that can be determined to correspond to operation by a
passenger (and/or correspond to operation by a passenger of a
particular device), such as the various determinations described in
detail herein. By way of example, if no correlation (or,
alternatively, no negative correlation) is identified between
various typing tendencies and the speed, acceleration, and/or
maneuvering of a traveling vehicle, and/or a certain typing
accuracy threshold it met and/or maintained over a period of time,
it can be concluded that the user is likely a passenger. [0243] (f)
The device 105 is restricted to operating only when it can be
determined based on one or more inputs that the device is under the
control of a passenger and/or under the control of a passenger
using this particular device, such as the various determinations
described in detail herein. By way of example, if relatively little
"shake" is perceived at mobile device 105 over a period of time, it
can be determined that the device is under the control of a
passenger, as a passenger has the ability to control "shake" by
using both hands to steady the device--an option not always
available to drivers who generally need their second hand to steer
the vehicle.
[0244] It should also be understood that the various restrictions
referenced herein can also be dependent upon the presence and/or
absence of certain of the determinations disclosed herein. Thus,
for example, various restrictions can be employed only when a
device cannot be definitively determined to be in the rear or on
the right side of a vehicle (thus suggesting that a driver can
potentially be operating the device).
EXAMPLE 5
[0245] In determining vehicle class or type, in certain
arrangements a determination is made as to whether one or more
mobile devices 105, 160 is/are present and/or in use in a vehicle.
If such a determination is affirmatively made, a further
determination can then be made regarding the general type or class
of the vehicle (e.g., motorcycle, car, bus, train, boat, plane,
etc.). This determination can then be used to further determine if
there are restrictions on the mobile device usage on the part of a
driver or the passenger in the vehicle. For example, if it is
determined through a signature analysis (that is, an analysis of
various patterns in various inputs) of an accelerometer 145A and/or
gyroscope 145B and/or GPS 145C of mobile devices 105 and/or 160
that there is a high-likelihood that a particular mobile device
105, 160 is located on a train, then that the mobile device 105,
160 can remain fully operational without any operation state
restrictions (assuming that no restrictions apply to anyone on the
train including the conductor). If however, it is determined that a
mobile device 105, 160 is being used within a car, restrictions can
be applied (e.g., no phone use at all or just no texting),
particularly if it is determined that the user of the mobile device
105, 160 is the driver of the car, and not a passenger.
[0246] As described in detail above, the type or class of vehicle
in which a mobile device 105, 160 is located can preferably be
identified and/or determined by using one or more of sensors 145 of
mobile device 105. In certain arrangements, this
identification/determination can be improved by using the onboard
sensors of other mobile devices 160 and/or the onboard sensors
(e.g., vehicle data system 164) of the vehicle in which mobile
device 105 is traveling. As noted above, being that different
vehicles operate in perceptibly different ways (which, in turn,
reflect different patterns that are perceptible to one or more of
sensors 145), the signature of one or more of sensors 145 of mobile
device 105 (and/or other mobile devices 160) present and/or used in
relation to each of the following vehicles is identifiable within a
certain degree of accuracy:
[0247] Train--The accelerometer signature of a mobile device 105
travelling in a train is distinct in that trains generally
accelerate and decelerate in the path of their movement (along the
Y-axis) relatively infrequently (being that trains are generally in
motion and maintain relatively constant speeds throughout their
route) and generally accelerate/decelerate at relatively consistent
rates. In addition, a train generally exhibits far less
acceleration along its X-axis (that is, perpendicular to its line
of motion) than other vehicles like cars and buses. Trains'
gyroscopic pitch and roll as perceived on gyroscope 145B are close
to zero (relative to cars and buses), while their gyroscopic yaw is
smaller than those of other vehicles like cars and buses. Moreover,
because a train travels on railroad tracks, its GPS location and
movement can be tracked and compared with known railroad tracks. In
addition, it can generally be expected that a train will have
multiple mobile device 160 in use on it. Finally, the sounds heard
on microphone 145D, are different for a train (other trains, train
track noise, little other traffic) than for other vehicles.
[0248] Airplane--The accelerometer signature of a mobile device 105
in an airplane is distinct in that the speed at which an airplane
travels (as can be determined in different ways, such as using
inputs from GPS 145C) is far higher than the speed at which most
other vehicles travel. Also, the height at which a commercial
airplane travels is far higher than the height at which other
vehicles travel, which can be sensed by the altitude sensor 1451
and/or the pressure sensor 145J and/or GPS sensor 145C.
Additionally, while other vehicles such as cars and/or trains
travel along paths (such as roads or railroad tracks) that can be
tracked/confirmed by overlaying GPS data with road/railroad map
data, airplanes travel along air-corridors that generally do not
align with any road for any appreciable distance. Also, changes in
speed (as can be measured by the Y-axis accelerometer 145A)
experienced in an airplane are generally much less frequent and
more gradual than the change of speed in other vehicles. The
movement signature of an airplane can be as characterized, for
example, by its X-acceleration (as perceived by accelerometer 145A)
and changes in pitch and roll (as perceived by gyroscope 145B), are
very different than those of other vehicles (airplanes have larger
values of pitch from takeoffs and larger rolls in turns than other
vehicles). In addition, airplanes generally take off and land at an
airport, which can be identified using mobile device 105 based on
the travel path detected by GPS 145C and the information from other
sensors 145 of mobile device 105, and/or from those of other mobile
devices 160 in the airplane. Finally, commercial airplanes
generally have multiple cell phones onboard and engine sounds that
are different than those of other vehicles.
[0249] It should be noted that while in other vehicles only the
driver is discouraged/prohibited from operating a mobile device
while driving, current airline protocol prohibits the use of all
mobile devices 105, 160 at certain times, such as while the
airplane is in motion. As such, the methods and systems disclosed
herein can effectively enforce the appropriate regulatory protocols
and/or guidelines and restrict and/or block one or more operations
of mobile devices 105, 160 of all users on an airplane.
[0250] Bus--The accelerometer signature of a mobile device 105
traveling on a bus is similar to that of a car, but substantially
different from that of other vehicles. Like a car, a bus can change
speeds (perceived by changes in the Y-axis accelerometer 145A)
relatively frequently. However, unlike in a car, in many situations
and scenarios relatively many mobile devices 105, 160 can be
present within a bus. Additionally, owing to the relatively large
size of a bus (as compared to a car), the acceleration,
deceleration and lane changes (perceived by X-axis accelerometer
145A) of a larger bus can be relatively more smooth and gradual
that other vehicles such as a car. The gyroscopic pitch, as
perceived by gyroscope 145B, is generally less than for a bus than
for a car. The signature of the bumps experienced in a bus (as
perceived by accelerometer 145A and gyroscope 145B) is different
than those in a car because the wheelbase of a bus is generally
much larger than the wheelbase of a car (for example, the time
between a bus' front wheels hitting a speed bump and its rear
wheels hitting the same speed bump is longer than the same for a
car travelling over the same speed bump at the same speed).
Furthermore, intra-city buses generally stop with relatively high
frequency, and this pattern can be easily detected by the onboard
cell phone sensors. The sounds perceived by microphone 145D of a
mobile device located in bus (e.g., engine sounds) are different
than those of other vehicles. The height of a mobile device in a
bus (which can be sensed by the altitude sensor 1451 and/or the
pressure sensor 145J and/or GPS sensor 145C), is generally greater
than the altitude of a mobile device in a car.
[0251] Truck--The accelerometer and gyroscope signatures of a
mobile device 105 traveling in a truck is substantially similar to
that of a bus. However, it is expected that there will be
relatively fewer mobile devices 105, 160 in a truck and a truck
will generally stop less frequently than a bus. The sounds
perceived by microphone 145D of a mobile device located in a truck
(e.g., engine sounds) are different than those of a bus. Finally
trucks will generally have more wheel axles than buses (because
they generally carry greater weight) and, as such, the bump
signature (as discussed in the Bus section above) for trucks will
be different than that of buses.
[0252] Car--The accelerometer signature of a mobile device 105
traveling in a car is similar to that of a bus, except that the
acceleration and deceleration movements detected by accelerometer
145A, as well as lateral movements detected by gyroscope 145B (such
as lane-changes) are expected to be relatively quicker and more
abrupt, being that cars are generally lighter and more "nimble" as
compared to a bus. The gyroscopic pitch, as perceived by gyroscope
145B, is generally greater for a car than for a bus. The signature
of the bumps experienced in a car (as perceived by accelerometer
145A and gyroscope 145B) is different than those in a bus because
the wheelbase of a car is generally much shorter than the wheelbase
of a bus (for example, the time between a car' s front wheels
hitting a speed bump and its rear wheels hitting the same speed
bump is shorter than the same for a bus travelling over the same
speed bump at the same speed)
[0253] Motorcycle--The accelerometer signature of a mobile device
105 traveling on a motorcycle is distinct in that the
Y-acceleration perceived by accelerometer 145A tends to be higher
than on cars, given the greater acceleration capabilities of most
motorcycles. In addition, motorcycles generally produce constant
small, jerky lateral movements (X-accelerations perceived by
accelerometer 145A) and gyroscopic rolls (as perceived by gyroscope
145B) because motorcycles require constant micro and macro steering
adjustments or corrections to remain upright. The signature of the
bumps experienced in a motorcycle (as perceived by accelerometer
145A and gyroscope 145B) is different than those in a car because
the wheelbase of a motorcycle is generally much shorter than the
wheelbase of a car (for example, the time between a motorcycle's
front wheels hitting a speed bump and its rear wheels hitting the
same speed bump is shorter than the same for a car travelling over
the same speed bump at the same speed). A truck will generally stop
less frequently than a bus. The sounds perceived by microphone 145D
of a mobile device located on a motorcycle (e.g., engine sounds)
are different than those of a car, in part because the mobile
device is not enclosed in a vehicle. It can be expected that there
will be relatively few mobile devices 105, 160 on a motorcycle, in
addition to the fact that the common use of full-faced helmets by
motorcycle riders, and the accompanying wind noise, decrease the
likelihood of the use of mobile devices 105, 160 by riders on a
motorcycle. It should also be noted that various communication
systems are available for motorcycle riders that integrate
earpieces and microphones into protective helmets.
[0254] Bicycle--The accelerometer signature of a mobile device 105
traveling on a bicycle is similar to a motorcycle, except that its
overall acceleration(s) and speed are much lower. Also, the act of
pedaling a bicycle generates a unique accelerometer and gyroscopic
signature including a regular lateral frequency as the weight of
the rider involuntarily shifts side to side as the user rotates the
crank to propel the bike. The sounds perceived by microphone 145D
of a mobile device located on a bicycle (e.g., no engine sounds)
are different than those of a car, in part because the mobile
device is not enclosed in a vehicle.
[0255] Boat--On a boat, the GPS 145C of mobile device 105 can
indicate that the boat is at constant altitude (zero altitude if
the boat is on an ocean) and located over water. The accelerometer,
gyroscopic and/or GPS signature of a mobile device 105 on a boat is
also distinct in that a boat generally remains at sea level (or
lake level), and rarely are altitude changes perceived, beyond
small waves. Additionally, when the boat is stopped (anchored) at
sea (as can be identified, for example, by location data from GPS
145C), its accelerometer(s) 145A can still show non-zero reading
(accounting for waves, etc.) whereas the same is generally untrue
for other vehicles. The "bump signature" of boats (as caused by
waves) is very different than that of other vehicles, in part,
because boats do not have wheels.
[0256] In addition, and as partially described above, the vehicle
class within which a mobile device 105 is traveling can be
discovered by one or more sound signatures picked up through mobile
devices 105, 160 (such as through microphone 145D) in such vehicle.
Different vehicles classes can be discerned through an analysis of
the sounds (e.g., engines, echoes, keystrokes) received by mobile
device(s) 105, 160 inside a vehicle (e.g., airplane jet engine
noise, car engine noise) and/or by the "white" or background noise
perceived by mobile devices 105, 160 within the vehicle. For
example, the white noise perceived in a bus with many passengers is
substantially different than white noise perceived in a car with
few people in it. The following Table 1 provides a synopsis of much
of the above referenced vehicle determination characteristics in
relation to several of sensors 145:
TABLE-US-00001 TABLE 1 Number of In- Vehicle Engine Sounds &
Mobile Environment Accelerometer (along X, Y, Gyroscope (around
Devices Sounds (White Vehicle and Z-axes) X, Y and Z axes) GPS
Likely Noise) Train X: Minimal changes Pitch: Very limited Known/
Many Environment sounds Y: Smooth changes in Roll: Very limited
identifiable (movement of tracks, acceleration Yaw: Less than other
path in-train passenger Z: Minimal changes vehicles. noises) are
perceptible. Airplane X: Turns have acceleration Pitch: Limited
High speed Many/ Engine sounds together with gyroscopic roll. Roll:
Constant falling High altitude None detectable. In-plane Y: High
speed. Minimal and correcting High passenger noises acceleration.
Especially pronounced acceleration detectable. Z: more pronounced
than in in turns takeoff and terraneous vehicles Yaw: generally
much landing slower than in events in terraneous vehicles known
locations Bus X: less than cars. Pitch: less than car Altitude of
Many Engine sound Y: More pronounced occupants in detectable, sound
of changes than car due to stops most buses doors opening generally
detectable. White higher than in noise detectable and cars. Buses
differentiable. are longer than cars (bumps felt differently) Truck
Similar to bus, but Truck will Pitch: less than car Unknown Few
Engine sound also show different Altitude of detectable. White
accelerometer signature on occupants in noise similar to car.
braking than bus and most trucks generally make fewer stops.
generally higher than in cars. Trucks arelonger thancars (bumps
felt differently) Car X: Quick and relatively Few jerky. Motorcycle
X: Constantly falling and Pitch: Limited 1-2 Sound of engine
correcting. Roll: Constant falling detectable and noise Y: Similar
to car, but with and correcting of road detectable larger
acceleration and (no enclosure). deceleration Speeds and Z:
Constantly falling and accelerations much correcting. higher than
bicycle. Bicycle X: Constantly falling and Pitch: Limited 1-2 No
engine noise and correcting. Roll: Constant falling noise of
environment Y: Similar to car, but with and correcting detectable.
Speeds smaller acceleration and and accelerations deceleration much
lower than Z: Constantly falling and motorcycle. correcting. Boat
Z: Minimal, different bumps Pitch: Constant falling Over water Many
Noise of water and signatures. and correcting - Zero altitude sound
echoes from though general smaller or lake water detectable than
roll altitude Roll: Constant falling unless and correcting moving
on a river.
[0257] It should be understood that Table 1 can be expanded to
include other vehicles such as ferries, forklifts, hovercrafts,
Segways, skateboards, rollerblades, etc.
[0258] It should be further understood that while much of the above
disclosure has referenced the identification of a driver/passenger
within a car, such disclosures can generally be similarly applied
to practically any setting and/or scenario involving practically
any vehicle, such as those referenced in Table 1.
[0259] At this juncture, it should be noted that although much of
the foregoing description has been directed to systems and methods
for determining user roles and/or devices usages within the context
of vehicular travel, the systems and methods disclosed herein can
be similarly deployed and/or implemented in scenarios, situations,
and settings far beyond the referenced scenarios. It can be readily
appreciated that the user-role determination system 100 can be
effectively employed in practically any scenario where the
determination and/or identification of a user or usage of a mobile
device is of value, such as in the context of exercising or game
playing. It should be further understood that any such
implementation and/or deployment is within the scope of the systems
and methods described herein.
[0260] It is to be understood that like numerals in the drawings
represent like elements through the several figures, and that not
all components and/or steps described and illustrated with
reference to the figures are required for all embodiments or
arrangements. It should also be understood that the embodiments
and/or arrangements of the systems and methods disclosed herein can
be incorporated as a software algorithm, application, program,
module, or code residing in hardware, firmware and/or on a computer
useable medium (including software modules and browser plug-ins)
that can be executed in a processor of a computer system or a
computing device to configure the processor and/or other elements
to perform the functions and/or operations described below. It
should be appreciated that according to at least one embodiment,
one or more computer programs or applications that when executed
perform methods of the present invention need not reside on a
single computer or processor, but can be distributed in a modular
fashion amongst a number of different computers or processors to
implement various aspects of the systems and methods disclosed
herein.
[0261] Thus, illustrative embodiments and arrangements of the
present systems and methods provide a computer implemented method,
computer system, and computer program product for deploying one or
more dynamic experiences within a restaurant. The flowchart and
block diagrams in the figures illustrate the architecture,
functionality, and operation of possible implementations of
systems, methods and computer program products according to various
embodiments and arrangements. In this regard, each block in the
flowchart or block diagrams can represent a module, segment, or
portion of code, which comprises one or more executable
instructions for implementing the specified logical function(s). It
should also be noted that, in some alternative implementations, the
functions noted in the block may occur out of the order noted in
the figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts, or combinations of special
purpose hardware and computer instructions.
[0262] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the invention. As used herein, the singular forms "a", "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising", when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
[0263] It should be noted that use of ordinal terms such as
"first," "second," "third," etc., in the claims to modify a claim
element does not by itself connote any priority, precedence, or
order of one claim element over another or the temporal order in
which acts of a method are performed, but are used merely as labels
to distinguish one claim element having a certain name from another
element having a same name (but for use of the ordinal term) to
distinguish the claim elements.
[0264] Also, the phraseology and terminology used herein is for the
purpose of description and should not be regarded as limiting. The
use of "including," "comprising," or "having," "containing,"
"involving," and variations thereof herein, is meant to encompass
the items listed thereafter and equivalents thereof as well as
additional items.
[0265] The subject matter described above is provided by way of
illustration only and should not be construed as limiting. Various
modifications and changes can be made to the subject matter
described herein without following the example embodiments and
applications illustrated and described, and without departing from
the true spirit and scope of the present invention, which is set
forth in the following claims.
* * * * *