U.S. patent application number 15/455025 was filed with the patent office on 2017-09-14 for detection of anomaly related to information about location of mobile computing device.
The applicant listed for this patent is Google Inc.. Invention is credited to Jesse Boettcher, Timo Bruck, Mark Rajan Malhotra, Prashant Reddy.
Application Number | 20170264383 15/455025 |
Document ID | / |
Family ID | 59788658 |
Filed Date | 2017-09-14 |
United States Patent
Application |
20170264383 |
Kind Code |
A1 |
Reddy; Prashant ; et
al. |
September 14, 2017 |
DETECTION OF ANOMALY RELATED TO INFORMATION ABOUT LOCATION OF
MOBILE COMPUTING DEVICE
Abstract
In a method for detection of an anomaly related to information
about a location of a mobile computing device, the anomaly related
to the information about the location of the mobile computing
device can be detected by a processor of the mobile computing
device. A communication about the anomaly can be provided via a
user interface of the mobile computing device. The anomaly can be
caused by a bug in an operating system of the mobile computing
device. Notifications about the anomaly can be provided to a user
of the mobile computing device or other mobile computing devices
registered to a shared account.
Inventors: |
Reddy; Prashant;
(Pittsburgh, PA) ; Malhotra; Mark Rajan; (San
Mateo, CA) ; Boettcher; Jesse; (San Jose, CA)
; Bruck; Timo; (Mountain View, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Google Inc. |
Mountain View |
CA |
US |
|
|
Family ID: |
59788658 |
Appl. No.: |
15/455025 |
Filed: |
March 9, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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62305960 |
Mar 9, 2016 |
|
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62305975 |
Mar 9, 2016 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04W 68/005 20130101;
H04L 12/2823 20130101; H04W 64/003 20130101; H04W 4/029 20180201;
H04W 4/021 20130101 |
International
Class: |
H04B 17/318 20060101
H04B017/318; H04W 4/02 20060101 H04W004/02; H04W 68/00 20060101
H04W068/00 |
Claims
1. A method comprising: generating, by a mobile computing device,
an indicator of a location of the mobile computing device;
determining, by an application that interfaces with a premises
management system and is executing on the mobile computing device,
that the indicator is associated with an anomaly; and providing, by
a user interface of the mobile computing device to a user of the
mobile computing device, a notice of the anomaly.
2. The method of claim 1, wherein the generation of the indicator
of the location of the mobile computing device is based on data
received through an application programming interface of an
operating system executing on the mobile computing device.
3. The method of claim 1, wherein the anomaly is generated by an
improper operation of an operating system executing on the mobile
computing device.
4. The method of claim 1, wherein the anomaly comprises a loss of a
signal from which the location of the mobile computing device is
determined.
5. The method of claim 1, wherein: the anomaly comprises a loss of
signal from which the location of the mobile computing device is
determined; and a disabled location service of an operating system
of the mobile computing device or a disabled wireless radio of the
mobile computing device caused the loss of receipt of the
signal.
6. The method of claim 1, wherein the anomaly comprises a deviation
in the location of the mobile computing device from historical
information about the location of the mobile computing device.
7. The method of claim 1, wherein the anomaly comprises a
collection of data that exhibits a pattern that indicates a
deviation in the location of the mobile computing device from
historical information about the location of the mobile computing
device.
8. The method of claim 1, wherein: the anomaly comprises a
collection of data that exhibits a pattern that indicates a
deviation in the location of the mobile computing device from
historical information about the location of the mobile computing
device; the pattern comprises, within a duration of time, at least
a first indicator that the location of the mobile computing device
is a particular location, followed by a second indicator that the
location of the mobile computing device is other than the
particular location, followed by a third indicator that the
location of the mobile computing device is the particular
location.
9. The method of claim 1, wherein: the anomaly comprises a
collection of data that exhibits a pattern that indicates a
deviation in the location of the mobile computing device from
historical information about the location of the mobile computing
device; the pattern comprises, within a duration of time, at least
a first indicator that the location of the mobile computing device
is a particular location, followed by a second indicator that the
location of the mobile computing device is other than the
particular location, followed by a third indicator that the
location of the mobile computing device is the particular location;
the particular location is defined by a geo-fence; and the duration
of time is between substantially 4 to substantially 6 minutes.
10. The method of claim 1, wherein the notice comprises a
recommendation for remediating the anomaly.
11. The method of claim 1, wherein: the notice comprises a
recommendation for remediating the anomaly; and the recommendation
comprises a suggestion to change a setting of at least one
component of the premises management system through the
application.
12. The method of claim 1, further comprising: receiving, by the
mobile computing device, a selection by the user indicating the
indicator of the location of the mobile computing device is
accurate or inaccurate; and providing, by the mobile computing
device to a remote computing device, a record indicating the
anomaly is associated with the selection by the user.
13. The method of claim 1, further comprising receiving, by the
mobile computing device from a machine learning system executing on
a remote computing device, anomaly criteria, wherein the
determination that the indicator is associated with the anomaly is
based on the anomaly criteria.
14. The method of claim 1, further comprising: prior to the
generation of the indicator of the location of the mobile computing
device, providing, by the mobile computing device, to a remote
computing device executing a machine learning system, a record
indicating that a prior anomaly is associated with a selection by
the user indicating a prior indicator of the location of the mobile
computing device is accurate or inaccurate; and receiving, by the
mobile computing device from the machine learning system executing
on the remote computing device, anomaly criteria determined by the
machine learning system based on the record, wherein the
determination that the indicator is associated with the anomaly is
based on the anomaly criteria.
15. A non-transitory computer readable medium storing instructions
that, when executed by a processor, cause the processor to perform
operations comprising: generating, by a mobile computing device, an
indicator of a location of the mobile computing device;
determining, by an application that interfaces with a premises
management system and is executing on the mobile computing device,
that the indicator is associated with an anomaly; and providing, by
a user interface of the mobile computing device to a user of the
mobile computing device, a notice of the anomaly.
16. A system comprising: a computing device in communication with a
premises management system and comprising a processor; and a
non-transitory, computer-readable medium in communication with the
processor and storing instructions that, when executed by the
processor, cause the processor to perform operations comprising:
determining that operation of a location generation component of a
first mobile computing device is associated with an anomaly, the
first mobile computing device of a set of devices distinct from the
computing device and associated with the premises management
system; selecting a second mobile computing device from among the
set of devices; and providing to the second mobile device a notice
of the anomaly.
17. The system of claim 16, wherein the anomaly comprises at least
one selected from the group consisting of: an improper operation of
an operating system executing on the mobile computing device, a
loss of a signal from which the location of the mobile computing
device is determined, a disabled location service of an operating
system of the mobile computing device, a disabled wireless radio of
the mobile computing device, a deviation in the location of the
mobile computing device from historical information about the
location of the mobile computing device, and a collection of data
that exhibits a pattern that indicates a deviation in the location
of the mobile computing device from the historical information
about the location of the mobile computing device.
18. The system of claim 16, wherein the operations further
comprise: providing a request to the first mobile computing device
to generate an indicator of the location of the first mobile
computing device; and determining that the indicator has not been
received before an expiration of a threshold period of time,
wherein the determination that the operation of the location
generation component of the first mobile computing device is
associated with the anomaly is based on the determination that the
indicator has not been received before an expiration of the
threshold period of time.
19. The system of claim 16, wherein the operations further
comprise: providing a request to the first mobile computing device
to generate an indicator of the location of the first mobile
computing device; receiving the indicator of the location of the
first mobile computing device; comparing the received indicator to
an anomalous operating condition associated with the anomaly; and
determining, by the computing device, based on the comparison of
the received indicator to the anomalous operating condition, that
the received indicator satisfies the anomalous operating condition,
wherein the determination that the operation of the location
generation component of the first mobile computing device is
associated with the anomaly is based on the determination that that
the received indicator satisfies the anomalous operating
condition.
20. The system of claim 16, wherein the operations further comprise
preventing execution of an operation associated with the premises
management system based on the determination that the operation of
the location generation component of the first mobile computing
device is associated with the anomaly
21. The system of claim 16, wherein the operations further
comprise: determining that the operation of the location generation
component of the first mobile computing device is not associated
with the anomaly; and in response to the determination that the
operation of the location generation component of the first mobile
computing device is not associated with the anomaly, permitting
execution of an operation associated with the premises management
system
22. The system of claim 16, wherein the operations further
comprise: providing the notice of the anomaly to each device of the
set of devices other than the first mobile computing device.
23. The system of claim 16, wherein the association of the set of
devices with the premises management system comprises an account
maintained by a computing device in communication with the premises
management system and under which each mobile computing device of
the set of devices is registered.
24. The system of claim 16, wherein: the association of the set of
devices with the premises management system comprises an account
maintained by a computing device in communication with the premises
management system and under which each of the set of devices is
registered; and each device of the set of devices comprises a
mobile computing device associated with a member of a family.
25. The system of claim 16, wherein the operations further
comprise: receiving from the first mobile computing device, a
record indicating that a prior anomaly was associated with a
selection by a user of the first mobile computing device indicating
a prior indicator of a prior location of the first mobile computing
device was accurate or inaccurate, wherein the determination that
the operation of the location generation component of the first
mobile computing device is associated with the anomaly is based on
the received record.
26. The system of claim 16, wherein the operations further
comprise: determining, by a machine learning system in
communication with the computing device, anomaly criteria based on
a received record indicating that a prior anomaly was associated
with a selection by a user of the first mobile computing device
indicating a prior indicator of a prior location of the first
mobile computing device was accurate or inaccurate, wherein the
determination that the operation of the location generation
component of the first mobile computing device is associated with
the anomaly is based on the anomaly criteria.
Description
BACKGROUND
[0001] The advancement of electronic communication network
bandwidth capabilities in the last decade has fostered the
realization of premises management systems. Premises management
systems can allow automated control of components, such as, for
example, heating, ventilation, and air conditioning ("HVAC")
systems, lighting systems, home theater, entertainment systems, and
security systems. Premises management systems can include control
panels through which a user can input settings, preferences, and/or
scheduling information.
[0002] Additionally, the advancement of electronic communication
network bandwidth capabilities has enabled the development of
mobile computing devices such as, for example, tablet computers,
smartphones, and smart watches. Electronic communication networks
can allow such mobile computing devices to obtain information about
their locations. The combination of the portability of mobile
computing devices and the ability of these devices to obtain
information about their locations has encouraged the introduction
of applications that expand the functionality of these devices.
BRIEF SUMMARY
[0003] According to an implementation of the disclosure, a mobile
computing device can generate an indicator of a location of the
mobile computing device. An application that interfaces with a
premises management system and is executing on the mobile computing
device can determine that the indicator is associated with an
anomaly. The user interface of the mobile computing device can
provide to a user of the mobile computing device, a notice of the
anomaly.
[0004] According to an implementation of the disclosure, a
non-transitory computer readable medium can store instructions
that, when executed by a processor, cause the processor to perform
operations that can include generating, by a mobile computing
device, an indicator of a location of the mobile computing device;
determining, by an application that interfaces with a premises
management system and is executing on the mobile computing device,
that the indicator is associated with an anomaly; and providing, by
a user interface of the mobile computing device to a user of the
mobile computing device, a notice of the anomaly.
[0005] According to an implementation of the disclosure a system
can include a computing device in communication with a premises
management system and having a processor; and a non-transitory,
computer-readable medium in communication with the processor and
storing instructions that, when executed by the processor, cause
the processor to perform operations. The operations can include
determining that operation of a location generation component of a
first mobile computing device is associated with an anomaly, the
first mobile computing device of a set of devices distinct from the
computing device and associated with the premises management
system.
[0006] According to an implementation of the disclosure, a means
can be provided for generating, by a mobile computing device, an
indicator of a location of the mobile computing device;
determining, by an application that interfaces with a premises
management system and is executing on the mobile computing device,
that the indicator is associated with an anomaly; and providing, by
a user interface of the mobile computing device to a user of the
mobile computing device, a notice of the anomaly.
[0007] Additional features, advantages, and embodiments of the
disclosed subject matter are set forth or apparent from
consideration of the following detailed description, drawings, and
claims. Moreover, it is to be understood that both the foregoing
summary and the following detailed description are illustrative and
are intended to provide further explanation without limiting the
scope of the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] The accompanying drawings, which are included to provide a
further understanding of the disclosed subject matter, are
incorporated in and constitute a part of this specification. The
drawings also illustrate embodiments of the disclosed subject
matter and together with the detailed description serve to explain
the principles of embodiments of the disclosed subject matter. No
attempt is made to show structural details in more detail than may
be necessary for a fundamental understanding of the disclosed
subject matter and various ways in which it may be practiced.
[0009] FIG. 1 is a flow diagram of an example of a method for
detection of an anomaly related to information about a location of
a mobile computing device according to an implementation of the
disclosure.
[0010] FIG. 2 is a diagram of an example of an environment in which
detection of an anomaly related to information about a location of
a mobile computing device can be performed according to an
implementation of the disclosure.
[0011] FIG. 3 is a diagram of an example of a premises management
system according to an implementation of the disclosure.
[0012] FIG. 4 is a diagram of an example of an application-provided
interface, of a mobile computing device, used to provide a
recommendation for addressing an anomaly according to an
implementation of the disclosure.
[0013] FIG. 5 is a flow diagram of an example of a method for
detection of an anomaly related to information about a location of
a mobile computing device in which an indication of an occurrence
of the anomaly is recorded in a memory according to an
implementation of the disclosure.
[0014] FIG. 6 is a block diagram of an example of a system for
detection of an anomaly related to information about a location of
a mobile computing device according to an implementation of the
disclosure.
[0015] FIG. 7 shows a block diagram of components of a premises
management system and computing devices linked to the premises
management system according to an implementation of the
disclosure.
[0016] FIG. 8 shows a sequence diagram for providing notifications
to devices associated with a premises management system according
to an implementation of the disclosure.
[0017] FIG. 9 shows a sequence diagram for providing notifications
to devices associated with a premises management system according
to an implementation of the disclosure.
[0018] FIG. 10 shows a sequence diagram for providing notifications
to devices associated with a premises management system according
to an implementation of the disclosure.
[0019] FIG. 11 shows a procedure in accordance with an
implementation of the disclosure.
[0020] FIG. 12 shows a procedure in accordance with an
implementation of the disclosure.
[0021] FIG. 13 is a block diagram of an example of a premises
management device according to an implementation of the
disclosure.
[0022] FIG. 14 is a block diagram of an example of a premises
management system according to an implementation of the
disclosure.
[0023] FIG. 15 is a block diagram of an example of a computing
device suitable for implementing certain devices illustrated in
FIGS. 1-14 according to an implementation of the disclosure.
DETAILED DESCRIPTION
[0024] According implementations of the disclosure, a premises
management system may be a computer implemented, networked system
of components that can control one or more components and
subsystems of a premises. For example, a premises management system
can control a home security system that manages one or more door
sensors, window sensors, motion sensors, cameras, and related
security components. The premises management system and/or the
security system can operate in various modes depending on the
occupancy of the home. For example a higher security mode may be
entered when no occupants are determined to be at the home.
Occupancy can be determined based on location indicators generated
by one or more mobile computing devices the occupants typically
carry with them. If a location indicator shows an occupant's mobile
device to be in the home, then the security system can determine
that the occupant is in the home. If a location generation
component of an occupant's mobile device is not operating
correctly, then the occupancy of the home may be incorrectly
determined, and thus the security mode may be incorrectly
determined.
[0025] Location generation components of mobile devices, such as
location services, often operate in the background of a mobile
device. Thus it may be difficult for a user to determine whether
the mobile device is generating accurate location indicators, or
whether location indicators are being generated at all. The
premises management system may rely on the provided location
indicators for the basis for determining the location of the mobile
device, and thus it may similarly be difficult for the premises
management system to determine whether the location indicators are
accurate.
[0026] The improper operation of a location generation component
may be linked to information about the mobile device, such as data
about a state of the mobile device, the frequency that location
indicators are generated, or the content of the location
indicators. Linked information may be inconsistent with proper
functioning of the location generation components of the mobile
device or otherwise correlated with the improper functioning
location generation components. Such linked information may be
deemed an anomaly. By detecting an anomaly in information about a
mobile device, it may be inferred that the location generation
component is improperly functioning. Thus, by detecting an anomaly
in information about a mobile device, the anomaly can be associated
with the location generation component of the mobile device or a
location indicator generated by the location generation
component.
[0027] Implementations of the disclosure can provide for
determining that a location identifier or operation of a location
generation component of a mobile computing device is associated
with an anomaly. These determinations may be made in
implementations of the disclosure by the mobile device itself, such
as via an application executing on the mobile device, or by a
computing device in communication with a premises management
system, such as where the computing device is a component of the
premises management system or a server remote from the premises
management system.
[0028] Implementations of the disclosure can take various actions
in response to determining that a location identifier or operation
of a location generation component of a mobile computing device is
associated with an anomaly, according to implementations of the
disclosure. For example, a user of the mobile device can be
notified, the mobile device can be prevented from providing further
location indicators to the premises management system, an
instruction can be provided to the mobile device to remediate the
improperly functioning location generation component, or
instructions can be provided to the premises management system or
subsystems and components thereof to remediate consequences of the
improperly functioning location generation component.
[0029] In an implementation of the disclosure, an application may
execute on a mobile computing device to interface with a premises
management system. Through such an interface, a premises management
system can be configured to control automatically various
components included in the premises management system. Such
automatic control of components of the premises management system
can take into consideration a location of the mobile computing
device, which can be interpreted by the premises management system
as a proxy for a location of a user of both the mobile computing
device and the premises management system. For example, if the
premises management system receives information about the location
of the mobile computing device that indicates that the mobile
computing device, and by proxy the user, is different from a
location of the components controlled by the premises management
system (e.g., premises of the user), then the premises management
system can cause one or more of the components of the premises
management system to change state. For example, the premises
management system can cause a security system of the premises
management system to be armed. For example, the premises management
system can cause a camera associated with the security system to
commence recording. For example, the premises management system can
cause a thermostat of the premises management system to reduce a
temperature setting. For example, the premises management system
can cause a notification about a condition of the premises (e.g., a
potential intruder) to be communicated to the user and/or to a
security agency.
[0030] Because automatic control of components of the premises
management system can take into consideration the location of the
mobile computing device, problems can arise if the information,
received by the premises management system, about the location of
the mobile computing device is erroneous. Aspects disclosed herein
describe a method and a system for detection of an anomaly related
to the information about the location of the mobile computing
device. A component of the mobile computing device such as a
location service can generate an indicator of a location of the
mobile computing device. An application executing on the mobile
computing device and interfacing with a premises management system
may determine that the indicator of the location is associated with
an anomaly. The mobile computing device may provide a communication
such as a notice about the anomaly to a user of the mobile
computing device via a user interface of the mobile computing
device.
[0031] FIG. 1 is a flow diagram of an example of a method 100 for
detection of an anomaly related to information about a location of
a mobile computing device according to an implementation of the
disclosure. In the method 100, at an operation 102, the anomaly
related to the information about the location of the mobile
computing device can be detected by a processor of the mobile
device. The information about the location of the mobile computing
device can be determined by a location generating component such as
a location service that utilizes location data and/or triangulation
and/or trilateration techniques applied to signals received from
components in a cellular network; location data from a WiFi.TM.
network, location data from a space-based navigation system (e.g.,
the Global Positioning System), or any combination thereof. In some
implementations, the generation of the indicator of the location of
the mobile computing device may be based on data received through
an application programming interface of an operating system
executing on the mobile computing device.
[0032] In an aspect of an implementation of the disclosure an
anomaly may be a bug or other improper operation of an operating
system of the mobile computing device or may be caused by a bug or
improper operation of an operating system. In an aspect, the mobile
computing device can be a tablet computer, a smartphone, or a
personal digital assistant. For example, the mobile computing
device can be one of a Nexus.TM. 5 smartphone, a Nexus.TM. 5x
smartphone, a Nexus.TM. 6 smartphone, a Nexus.TM. 6p smartphone, or
other Nexus' model smart phone or tablet.
[0033] An indicator of a location of a mobile computing device may
be associated with an anomaly, when, for example, the indicator is
generated when the anomaly is present. In an aspect of an
implementation of the disclosure, the anomaly can include one or
more of a loss of receipt of a signal from which the location of
the mobile computing device is determined, a deviation in the
location of the mobile computing device from historical information
about the location of the mobile computing device, or a collection
of information that exhibits a pattern that indicates the
deviation.
[0034] In some implementations, where the anomaly comprises a
collection of data that exhibits a pattern, the pattern can
include, within a duration of time, at least a first indicator that
the location of the mobile computing device is a particular
location, followed by a second indicator that the location of the
mobile computing device is other than the particular location,
followed by a third indicator that the location of the mobile
computing device is the particular location. In some
implementations the particular location may be defined by a
geofence and the duration of time can be a specified period of
time, such as between substantially four to substantially six
minutes.
[0035] In some implementations an anomaly may include or be caused
by a disabled location service of an operating system or a disabled
wireless radio of the mobile computing device. For example, if the
mobile device has an iOS.RTM. operating system, then the loss of
receipt of the signal can be caused a disablement of a location
services module of the iOS.RTM. operating system. For example, if
the mobile device has an Android.TM. platform, then the loss of
receipt of the signal can be caused by a cessation of power to a
WiFi.TM. module of the Android.TM. platform.
[0036] In some implementations an anomaly may include
inconsistencies between components of a mobile device. For example,
the mobile device may provide a location indicator of a geofence
crossing event, but the device may also indicate that there is no
wireless connectivity.
[0037] Other anomalies may include, according to implementations of
the disclosure, an expired credential of a mobile device such as a
credential necessary to log into a wireless network or connect to
an application account; an incorrectly registered premises location
such that occupants are at home but their premises is indicated as
located in a different city; or other erroneous events or
inconsistent settings of devices, networks, or systems such as are
suitable for the purposes of the disclosure.
[0038] FIG. 2 is a diagram of an example of an environment 200 in
which detection of an anomaly related to information about a
location of a mobile computing device can be performed according to
an implementation of the disclosure. The environment 200 can
include several elements such as, for example, a mobile computing
device 202 and a premises management system 204. In an
implementation, an element of the environment 200 can be
communicatively connected to one or more other elements via a
network 206.
[0039] The network 206 can be, for example, a telecommunications
network configured to allow computers to exchange data. Connections
between elements of the environment 200 via the network 206 can be
established using cable media, wireless media, or both. Data
traffic on the network 206 can be organized according to a variety
of communications protocols including, but not limited to, the
Internet Protocol Suite (Transmission Control Protocol/Internet
Protocol (TCP/IP)), the Institute of Electrical and Electronics
Engineers (IEEE) 802 protocol suite, the synchronous optical
networking (SONET) protocol, the Asynchronous Transfer Mode (ATM)
switching technique, or any combination thereof. In an embodiment,
the network 206 can include the Internet, a cellular network, a
WiFi.TM. network, or any combination thereof.
[0040] Through an interface (not illustrated) presented on the
mobile computing device 202, one or more components of the premises
management system 204 can be controlled automatically via one or
more signals transmitted from the mobile computing device 202 to
the premises management system 204 via the network 206.
Additionally or alternatively, control of one or more aspects of
one or more components of the premises management system 204 can be
performed automatically in response to a location of the mobile
computing device 202, which can be interpreted by the premises
management system 204 as a proxy for a location of a user of both
the mobile computing device 202 and the premises management system
204.
[0041] FIG. 3 is a diagram of an example of the premises management
system 204 according to an implementation of the disclosure. The
premises management system can be installed within premises that
include a house or other structure 302. The system 204 can
implement subsystems, including a security system, via multiple
types of premises management devices, such as one or more
intelligent, multi-sensing, network-connected thermostats 304, one
or more intelligent, multi-sensing, network-connected hazard
detection units 306, one or more intelligent, multi-sensing,
network-connected entry detection units 308, one or more
network-connected door handles 310, one or more intelligent,
multi-sensing, network-connected cameras 312, one or more
intelligent, multi-sensing, network-connected controller devices
314, or any combination thereof.
[0042] Data from any of these premise management devices can be
used by the security system, as well as for the respective primary
functions of the premise management devices. For example, the
security system can manage the arming, disarming, and activation of
alarms and other security aspects of the premises, and other
systems of the premises management system 204 can handle aspects
such as light, temperature, and hazard detection of the premises.
The premises management system 204 can leverage data obtained in
one subsystem to improve the functionality of another
subsystem.
[0043] For example, data from the sensors can be used to determine
the occurrence of a security breach or security related event, such
as entry through a window of the premises, lengthy presence of an
individual in an unusual location and an unusual time, or tampering
with a lock of a door of the premises, etc. Upon the occurrence of
such an event, the security system can determine, based on any of
various algorithms, that an alarm is warranted and enter an alarm
mode, which can include automatically notifying a third party
monitoring service as well as operating components of the system to
provide visual and/or audible alerts, such as a siren sound,
repeated beeping sound, or flashing lights.
[0044] Additionally, the security system can determine where a
security breach has occurred and thereafter track the location of
the unauthorized party, as well as the locations of authorized
parties within and/or around the premises. Additionally, in view of
the high stress levels that can accompany experiencing an
unauthorized intrusion, the security system can announce the
location of the security breach and the location of the
unauthorized party within the premises. In so doing the authorized
occupants are automatically warned of which locations in/around the
premises to avoid and the unauthorized party is simultaneously
deterred from further advance due to the clear notice to the
unauthorized party that he/she is being tracked. Alternatively, the
location of the unauthorized party can be announced only to select
devices so as to inform an authorized user while leaving the
unauthorized party unaware that he/she is being tracked.
[0045] The security system can be operable to function in any of
various modes or states. For example, security system modes can
include "stay", "away", "vacation", "home", and "sleep" modes. In a
"stay" mode the security system can operate under the assumption
that authorized parties are present within the premises but will
not be entering/leaving without notifying the system; therefore
data from certain interior sensors can be given lower weight in
determining whether an unauthorized party is present. In an "away"
mode the security system can operate under the assumption that no
authorized parties are in the premises; therefore data from all
sensors, interior and exterior, can be accorded high weight in
determining whether an unauthorized party is present. In a
"vacation" mode the security system can operate under the
assumption that no authorized parties are in the premises during a
specified period of time and/or with the exception of certain
specified parties such as pet sitters or house-watchers; therefore
data from all sensors, interior and exterior, can be accorded high
weight in determining whether an unauthorized party is present
during the specified period of time and with limited exceptions for
parties having specific identifying information. In a "home" mode
the security system can operate under the assumption that
authorized parties are within the premises and will be freely
entering/leaving the premises without notifying the system;
therefore data from certain sensors (interior and exterior) can be
accorded low weight in determining whether an unauthorized party is
present. In a "sleep" mode the security system can operate under
the assumption that authorized parties are within the premises and
will not be freely entering/leaving the premises without notifying
the system; however because the occupants may not be conscious that
data from certain interior sensors can be accorded low weight but
certain exterior sensors can be accorded high weight in determining
whether an unauthorized party is present. It should be understood
that these modes are merely examples and can be modified, removed,
or supplemented by other modes. In some implementations, the
security system may execute as a component of the premises
management system, and thus these modes may be modes of the
premises management system and function similarly.
[0046] Additionally, the security system can function in any of
various alarm states. For example, in a "green" or "low" alarm
state the security system can operate under the assumption that all
is well and no unauthorized parties have been detected
within/around the premises. In a "yellow" or "medium" alarm state
the security system can operate under the assumption that an
unauthorized party is potentially present in or around the
premises. In this state certain sensor data can be analyzed
differently or additional confirmations of authorization, such as
entering a code, can be required of to avoid escalation to a higher
alarm state. In a "red" or "high" alarm state the security system
can operate under the assumption that an unauthorized party has
been detected on the premises and preventive measures can be taken,
such as notifying a third party monitoring service and/or
activating an alarm and announcement, as will be described later.
It should be understood that greater or fewer gradients of alarm
state can be included. Hereinafter, a heightened alarm can refer to
an alarm state above the low alarm state.
[0047] At a high level, the premises management system 204 can be
configured to operate as a learning, evolving ecosystem of
interconnected devices. New premises management devices can be
added, introducing new functionality, expanding existing
functionality, or expanding a spatial range of coverage of the
system. Furthermore, existing premises management devices can be
replaced or removed without causing a failure of the system 204.
Such removal can encompass intentional or unintentional removal of
components from the system 204 by an authorized user, as well as
removal by malfunction (e.g., loss of power, destruction by
intruder, etc.). Due to the dynamic nature of the system, the
overall capability, functionality and objectives of the premises
management system 204 can change as the constitution and
configuration of the premises management system 204 change.
[0048] In order to avoid contention and race conditions among the
interconnected devices, certain decisions, such as those that
affect the premises management system 204 at a system level or that
involve data from multiple sources, can be centralized in the
aforementioned "brain" component. The brain component can
coordinate decision making across the system 204 or across a
designated portion thereof. The brain component is a system element
at which, for example, sensor/detector states can converge, user
interaction can be interpreted, sensor data can be received, and
decisions can be made concerning the state, mode, or actions of the
system 204. Hereinafter, the system 204 brain component can be
referred to as the "primary system processor" such as is shown with
respect to element 1410 in FIG. 14 below. The function of primary
system processor can be implemented in the controller device 314,
for example, hard coded into a single device, or distributed
virtually among one or more premises management devices within the
system using computational load sharing, time division, shared
storage, or other techniques.
[0049] However implemented, the primary system processor can be
configured to control subsystems and components of the premises
management system 204, such as, for example, the disclosed security
system and/or a system of a "smart home environment" as discussed
later portions of this disclosure. Furthermore, the primary system
processor can be communicatively connected to control, receive data
from, or transmit data to premises management devices within the
system, as well as receive data from or transmit data to
devices/systems external to the system 204, such as third party
servers, cloud servers, mobile devices, and the like.
[0050] In the embodiments disclosed herein, each of the premises
management devices can include one or more sensors. In general, a
"sensor" can refer to any device that can obtain information about
its local environment and communicate that information in the form
of data that can be stored or accessed by other devices and/or
systems. Sensor data can form the basis of inferences drawn about
the sensor's environment. For example, the primary system processor
can use data from a plurality of sensors, e.g., including entry
detection unit 308, to determine whether an unauthorized party is
attempting enter the house 302 through a window.
[0051] A brief description of sensors that may be included in the
premises management system 204 follows. Examples provided are not
intended to be limiting but are merely provided as illustrative
subjects. The premises management system 204 can use data from the
types of sensors in order to implement features of a security
system. The premises management system 204 can employ data from any
type of sensor that provides data from which an inference can be
drawn about the environment in or around a premises, such as house
302.
[0052] Generally, sensors can be described by the type of
information they collect. For example, sensor types can include
motion, smoke, carbon monoxide, proximity, temperature, time,
physical orientation, acceleration, location, entry, presence,
pressure, light, sound, and the like. A sensor also can be
described in terms of the particular physical device that obtains
the environmental information. For example, an accelerometer can
obtain acceleration information, and thus can be used as a general
motion sensor and/or an acceleration sensor. A sensor also can be
described in terms of the specific hardware components used to
implement the sensor. For example, a temperature sensor can include
a thermistor, thermocouple, resistance temperature detector,
integrated circuit temperature detector, or combinations
thereof.
[0053] A sensor further can be described in terms of a function or
functions the sensor performs within the premises management system
204. For example, a sensor can be described as a security sensor
when it is used to determine security events, such as unauthorized
entry.
[0054] A sensor can be operated for different functions at
different times. For example, the premises management system 204
can use data from a motion sensor to determine how to control
lighting in the house 302 when an authorized party is present and
use the data as a factor to change a security system mode or state
on the basis of unexpected movement when no authorized party is
present. In another example, the premises management system 204 can
use the motion sensor data differently when a security system mode
is in an "away" mode versus a "home" state, i.e., certain motion
sensor data can be ignored while the system is in a "home" mode and
acted upon when the system is in an "away" mode.
[0055] In some cases, a sensor can operate as multiple sensor types
sequentially or concurrently, such as where a temperature sensor is
used to detect a change in temperature, as well as the presence of
a person or animal. A sensor also can operate in different modes
(e.g., different sensitivity or threshold settings) at the same or
different times. For example, a sensor can be configured to operate
in one mode during the day and another mode at night. As another
example, a sensor can operate in different modes based upon a mode
or the disclosed security system, state of the premises management
system 204, or as otherwise directed by the primary system
processor.
[0056] Multiple sensors can be arranged in a single physical
housing, such as where a single device includes movement,
temperature, magnetic sensors such as magnetometers or compasses,
and/or other sensors. Such a housing can also be referred to as a
sensor, premises management device, or a sensor device. For
clarity, sensors can be described with respect to the particular
functions they perform and/or the particular physical hardware
used.
[0057] Returning to FIG. 1, as described above, in an aspect, the
anomaly can include a collection of information that exhibits a
pattern that indicates a deviation in the location of the mobile
computing device from historical information about the location of
the mobile computing device. For example, the pattern can include,
within a duration of time, at least a first indication that the
location of the mobile computing device is a particular location,
followed by an indication that the location of the mobile computing
device is other than the particular location, followed by a second
indication that the location of the mobile computing device is the
particular location. In a realization, the particular location can
be defined by a geo-fence. In a realization, the duration of time
can be five minutes.
[0058] For instance, if: (1) the particular location is the
premises of the user and (2) control of one or more aspects of one
or more components of a premises management system is performed
automatically in response to the location of the mobile computing
device, then having a situation in which the mobile computing
device receives an indication that the location of the mobile
computing device is other than the premises of user (when, in
actuality, the location of the mobile computing device is the
premises of the user) can cause the premises management system to
change a state of one or more components of the premises management
system. For example, with reference to FIG. 3, the premises
management system 204 can cause: (1) the security system of the
premises management system 204 to be armed, (2) the camera 312
associated with the security system to commence recording, (3)
thermostat 304 to reduce a temperature setting, (4) a notification
about a condition of the premises (e.g., a potential intruder) to
be communicated to the user and/or to a security agency, (5) the
like, or (6) any combination thereof. Such a situation can cause
problems if the location of the mobile computing device, and by
proxy the location of the user, in actuality is the premises of the
user.
[0059] Returning to FIG. 1, in the method 100, at an operation 104,
a communication about the anomaly such as a notice can be provided
via a user interface of the mobile computing device, according to
an implementation of the disclosure. The communication can be
visual, audible, tactile, or any combination thereof.
[0060] In an aspect of an implementation of the disclosure, in
response to a first instance of the operation 104, occurrence of a
second instance of the operation 104 can be delayed for a duration
of time. In a realization, the duration of time can be seven days.
For instance, if in a first instance in which the anomaly related
to the information about the location of the mobile computing
device is detected and the communication about the anomaly
associated with the first instance is provided, in a second
instance in which the anomaly related to the information about the
location of the mobile computing device is detected, the
communication about the anomaly associated with the second instance
can occur after a delay from a time at which the communication
about the anomaly associated with the first instance is
provided.
[0061] In an aspect of an implementation of the disclosure, the
communication about the anomaly can include a recommendation for
addressing or remediating the anomaly. For example, if the anomaly
includes a loss of receipt of a signal from which the location of
the mobile computing device is determined, then the recommendation
can be to restore reception of the signal. For instance, if the
mobile device has an iOS.RTM. operating system, then the
recommendation can be to enable a location services module of the
iOS.RTM. operating system. For instance, if the mobile device has
an Android.TM. platform, then the recommendation can be to restore
power to a WiFi.TM. module of the Android.TM. platform. For
example, if control of one or more aspects of one or more
components of a premises management system is performed
automatically in response to the location of the mobile computing
device, then the recommendation can include a suggestion to change
a setting of the one or more components of the premises management
system controlled through an application-provided interface of the
mobile computing device. FIG. 4 is a diagram of an example of an
application-provided interface 400, of a mobile computing device,
used to provide a recommendation for remediating or otherwise
addressing an anomaly, according to an implementation of the
disclosure.
[0062] Returning to FIG. 1, in an aspect, the operation 104 can be
in response to an activation, by the mobile computing device, of an
application-provided interface configured to control one or more
components of a premises management system. For instance, if the
method 100 is implemented by an application operating on the mobile
computing device, then the application can be operated to
continually monitor the information about the location of the
mobile computing device to detect an anomaly, but communication
about a detected anomaly can be in response to an activation, by
the mobile computing device, of an application-provided interface
configured to control one or more components of a premises
management system. Such activation of the application-provided
interface may occur later than a time at which the anomaly was
detected.
[0063] FIG. 5 is a flow diagram, according to an implementation of
the disclosure, of an example of a method 500 for detection of an
anomaly related to information about a location of a mobile
computing device in which an indication of an occurrence of the
anomaly is recorded in a memory. In the method 500, at the
operation 502, the anomaly related to the information about the
location of the mobile computing device can be detected by the
processor of the mobile device. At an operation 503, the indication
of the occurrence of the anomaly can be recorded in the memory of
the mobile computing device. At an operation 504, the communication
about the anomaly can be provided, via the user interface of the
mobile computing device, in response to a presence, in the memory
of the mobile device, of the indication of the occurrence of the
anomaly.
[0064] In an example, according to an implementation of the
disclosure, method 500 may be implemented by an application
operating on the mobile computing device. The application can be
operated to continually monitor the information about the location
of the mobile computing device to detect an anomaly. If the anomaly
is detected, then an indication of the occurrence of the anomaly
can be recorded in a memory of the mobile computing device.
Communication about a detected anomaly can be in response to a
presence, in the memory of the mobile device, of the indication of
the occurrence of the anomaly. Such a communication may occur later
than a time at which the anomaly was detected.
[0065] FIG. 6 is a block diagram of an example of a system 600 for
detection of an anomaly related to information about a location of
a mobile computing device according to an implementation of the
disclosure. The system 600 can include, for example, a processor
602, a user interface 604, and a bus 606. The processor 602 can
include any processing circuit operative to control an operation of
the system 600. The user interface 604 can be any type of interface
through which a user of the system 600 can input and/or receive
information. The information can be communicated through a visual
technique, an audible technique, a tactile technique, or any
combination thereof. The bus 606 can be coupled to the processor
602 and the user interface 604, and can be configured to facilitate
communications among these components. Other devices and components
(not illustrated) can be included in the system 600.
[0066] According to an implementation of the disclosure, processor
602 can be configured to detect the anomaly related to the
information about the location of the mobile computing device. The
anomaly may be any type of anomaly discussed herein or otherwise
suitable for the purposes of the disclosure. In an aspect, the
processor 602 and the user interface 604 can be configured to
provide, in response to an activation of an application-provided
interface configured to control at least one component of a
premises management system, a notice indicating the anomaly. In an
aspect of the disclosure, the system 600 can include a memory 608.
The memory 608 can be configured to record an indication of an
occurrence of the anomaly. In this aspect, the processor 602 and
the user interface 606 can be configured to provide the
communication about the anomaly, in response to a presence, in the
memory 608, of the indication of the occurrence of the anomaly. For
instance, if the system 600 is implemented by an application
operating on the mobile computing device, then the application can
be operated to continually monitor the information about the
location of the mobile computing device to detect an anomaly. If
the anomaly is detected, then an indication of the occurrence of
the anomaly can be recorded in the memory 608. Communication about
a detected anomaly can be in response to a presence, in the memory
608, of the indication of the occurrence of the anomaly. Such a
communication may occur later than a time at which the anomaly was
detected. Generally, the components of system 600 may implement any
of the methods and procedures disclosed herein, such as those
discussed with respect to FIGS. 1-5
[0067] Premises management systems may maintain accounts linking
each of a set of devices such as mobile computing devices. For
example, a premises management system may maintain a family account
that includes a mobile device belonging to or otherwise associated
with each member of the family living at a premises, such as a
home. The premises management system may be in communication with
each of the mobile devices in the family account and may be able to
determine that one of the mobile devices is not properly performing
an operation associated with the premises management system. For
example, operations executing on the mobile devices may provide
geofence location data to the premises management system and used
to make determinations about the family's home. The premises
management system may receive an indicator from a particular mobile
device that the particular mobile device has traversed a geofence
boundary over a threshold number of times, within a threshold
amount of time. As a result of exceeding these thresholds, the
premises management system may determine that the particular mobile
device is operating anomalously. The premises management system may
select each other mobile device registered to the family account
and provide to the selected devices a notice including an indicator
that the particular mobile device is operating anomalously.
Furthermore, while the particular mobile device is operating
anomalously, the premises management system may refrain from using
data received from the particular mobile device when making
determinations of the occupancy status of the home, such as whether
all family members are home or away from home as discussed
above.
[0068] A premises management system may include a computing device
that may communicate with one or more other devices, such as mobile
computing devices. For example, FIG. 7 shows, according to an
implementation of this disclosure, a block diagram of components of
a premises management system and computing devices linked to the
premises management system. Premises management system 700 may
include a computing device, which may be a home monitoring hub or
controller, such as controller 1412 described below with respect to
FIG. 14, and/or a remote system, such as remote system 1408
described below with respect to FIG. 14.
[0069] The premises management system may be in communication with
one or more other mobile devices 710, 720, 730. Mobile devices 710,
720, 730 may be, for example, mobile computing devices, such as
smart phones, tablets, or laptops; wearable computing devices, such
as watches, glasses, or computing devices integrated into shoes or
clothing; or any mobile device providing the functionality of a
"sensor" such as any of the sensor devices and related components
described below with respect to FIGS. 13-15.
[0070] Generally, implementations of this disclosure may be
partially or completely incorporated within a "smart home
environment", as is described in other portions of this disclosure
such as with respect to FIGS. 13-15. For example, in addition to
communicating with mobile devices 710, 720, 730, premises
management system 700 may communicate with various intelligent,
multi-sensing, network-connected devices, which can integrate
seamlessly with each other and/or with a central server or
cloud-computing system, such as any of the sensor devices and
related components described below with respect to FIGS. 13-15. By
incorporating or communicating with such components, premises
management system 700 may provide a variety of functionality, such
as home security, temperature control, fire detection, hazardous
substance detection, or any other functionality suitable for the
purposes of this disclosure.
[0071] In an implementation of the disclosure, mobile devices 710,
720, and 730 may each be associated with premises management system
700. For example, premises management system 700 may maintain an
account on a computing device in communication with the premises
management system 700, such as computing device local to the
premises or a remote system, such as a remote server. This account
may include a designator of an association between members, such as
a family account and include accounts for each family member who
lives in a particular home. Each family member may register her
computing device with the family account. For example, a parent may
own or otherwise be associated with mobile device 730, the parent's
older daughter may own or otherwise be associated with mobile
device 720, and the parent's younger daughter may own or otherwise
be associated with mobile device 710. Each mobile device 710, 720,
730 may be a mobile device the family member typically carries with
them, or any of the other mobile computing devices discussed
herein.
[0072] A family member may access the family account through, for
example, an interface displayed on a webpage or mobile application.
The family member may be required to enter a login, password, or
other credential that may be authenticated by a remote server of
the premises management system. The family member may provide or
verify identifying information for their associated mobile device.
For example, the older daughter may enter the phone number of
mobile device 720, or an application installed on mobile device 720
may obtain identifying information and communicate such information
to the family account. As another example, a local component of
premises management system 710 may access a local wireless network
to which mobile device 720 is connected, retrieve its identifying
information, and present such information for verification in the
interface of the family account.
[0073] In addition to family members, devices belonging to other
individuals may be registered with the family account. For example,
a child care provider's mobile device may be added or a lawn care
provider's mobile device may be added. Permissions or certain
functionality associated with accounts under the family account may
be configurable. For example, detection of certain registered
mobile devices within the home may generally disarm a security
system. However this disarming functionality may be disabled for
the child care provider's mobile device except when the child care
provider's device is detected at a time and/or place that
corresponds to a child care schedule accessible by the premises
management system.
[0074] In an implementation of this disclosure, certain
functionality of a premises management system, such as premises
management system 700, may be triggered by employing geofencing
techniques to determine an occupancy status of a home, such as
whether some or all occupants of a premises are either "home" or
"away" or whether the premises is in "vacation mode", "stay mode",
or "sleep mode" as discussed above with respect to FIGS. 1-5. The
location of an occupant may be based on the location of their
mobile device. For example, all occupants of a home, such as the
mother, oldest daughter, and youngest daughter described above, may
have mobile devices, such as mobile devices 710, 720, 730,
registered with a family account of premises management system 700.
Each mobile device 710, 720, 730 may perform operations that
provide data related to the location of the mobile device. For
example, a mobile device may have a GPS sensor that may provide
location data based on a GPS determined coordinate. A mobile device
may have a radio frequency identification (RFID) or other near
field communications (NFC) sensor, Bluetooth sensor, or Wi-Fi
sensor that may provide location data that may be determined based
on the proximity of a wireless network node to the sensor and the
range of the respective wireless protocol or standard employed by
the sensor. A mobile device perform operations that provide
location data based on the location of the nearest cellular network
node, such as a base station, to the mobile device and a range of
the respective protocol or standard, such as the cell size
currently being accessed on the cellular network.
[0075] Mobile devices 710, 720, 730 may transmit location data such
as that described above for the mobile devices 710, 720, 730 to the
premises management system 700. This location data may be used to
represent the location of each respective family member. Such
location data may be compared to predetermined location data for
the boundary of the home. If a family member's location data is
outside predetermined boundary location data for the home, then
that family member may be determined to be away. Similarly, if all
the family members' location data is outside the predetermined
boundary location data for the home, then all family members may be
determined to be away.
[0076] In another implementation of this disclosure, various
intelligent, multi-sensing, network-connected devices, which can
integrate seamlessly with each other and/or with a central server
or cloud-computing system, such as any of the sensor devices and
related components described below with respect to FIGS. 13-15, may
provide location data to the premises management system 700. For
example, camera sensors that are part of the smart home environment
may determine a location of a family member by identifying the
family member through facial recognition procedures and stored
predetermined location data for the location of the camera sensor.
In another example, audio sensors that are part of the smart home
environment may determine a location of a family member by
identifying the family member through voice recognition procedures
and stored predetermined location data for the location of the
audio sensor and the range of the audio sensor.
[0077] In another implementation, a family member may be identified
by components of premises management system 700 by detecting a
wireless identifier transmitted by her mobile device. When the
wireless identifier of a family member's mobile device is
identified on one side of a boundary of the home and then detected
at a later time on the other side, or not detected on the other
side for a threshold period of time, then the family member may be
determined to have traversed the boundary. If such boundary
represents the outer boundary of the home, then the family member
may be determined to be away.
[0078] In implementations of this disclosure, systems of a premises
management system and procedures within such systems may be
triggered when one or more occupants are determined to be away.
Such systems and procedures may incorporate various intelligent,
multi-sensing, network-connected devices, which can integrate
seamlessly with each other and/or with a central server or
cloud-computing system, such as any of the sensor devices and
related components described below with respect to FIGS. 13-15. For
example, an alarm system may be triggered when one or more
occupants are determined to be away, camera sensors of a home
monitoring system may be activated when one or more occupants or
all adult occupants are determined to be away, a thermostat setting
may be adjusted such that a heating or cooling system is caused to
activate or deactivate when some or all occupants are determined to
be away. Conversely, in implementations of this disclosure, systems
of a premises management system and procedures within such systems
may be triggered when one or more occupants are determined to be
home. For example, cameras within a child occupant's room in a home
monitoring system may be triggered when the child is determined to
be home, door and window lock sensors of a home security system may
be triggered when one or more occupants are determined to be home
and a time and date data are received that correspond to the
trigger, or active infrared sensors of a sleep monitoring system
may be triggered when an occupant is determined to be home and
family account data is stored that indicates the occupant has a
sleeping disorder and is to be monitored.
[0079] In light of the above, it may be beneficial for a premises
management system to determine when an operation of a family
member's mobile device associated with home and away determinations
is performing anomalously. For example, if a family member's mobile
device is providing a location signal indicating it is within a
boundary of the home, but the family member has left the home, the
security system may not be activated because the premises
management system may erroneously determine that the family member
is home. In another example, an operation of a mobile device of a
family member may not have updated the mobile device's location
since before the family member arrived home. Thus the premises
management system may erroneously determine the family member is
away, and as a result a camera sensor of a home monitoring system
may remain triggered and record the family member when they are
home without the family member's knowledge.
[0080] Anomalous location indicating operations of a mobile device
may be determined in a variety of ways. For example, if a request
related to an location identifying operation is provided to a
mobile device and a response is not received within a predetermined
threshold period of time, then the expiration of the threshold
period of time may be an indicator that the operation is not taking
place. As a result of this indicator, it may be determined that the
mobile device is operating anomalously. This may occur in
circumstances where, for example, a wireless or cellular network
interface is disabled on the device, the device is powered down, or
there is not network access for the device.
[0081] In an implementation of the disclosure, a request to perform
an operation associated with geofencing may be provided to the
mobile device. For example, the request may include an instruction
to perform an operation to provide a determination of whether a
geofence has been crossed a threshold number of times within a
threshold time period. These thresholds may represent anomalous
operating conditions and may have threshold values, for example of
at least three traversals in five minutes. Determining that the
anomalous condition has been met may result in determining the
device is operating anomalously.
[0082] In an implementation of the disclosure, the request may
include an instruction to provide a mobile device identifier to the
closest wireless network node, to determine a distance from the
closest Wi-Fi access node, or to determine a GPS location. These
operations may result in data indicating a location of the mobile
device or data that may be used with data about the location of
other network components to calculate the location of the mobile
device. For example the location of a wireless access node may be
known and the maximum distance from the node may be known based on
the specification of the network protocol being employed. Location
data such as this may be compared to other data indicating a
location of the mobile device. For example, a network identifier of
the mobile device may currently be detected within the home,
whereas GPS or cellular network data may indicate the device is
located outside of the home. These two locations may be compared
and determined to be incongruous, for example, they may be
different by more than a threshold amount. A determined incongruity
may be a condition that results in the mobile device being
determined to be operating anomalously.
[0083] Other sensor devices and related components of the smart
home environment may also be used to determine incongruity between
detected locations of the mobile device. For example, facial
recognition procedures or gait recognition procedures executing on
a camera device in the home may determine a family member is
present in the home, or voice recognition procedures executing on
an audio sensor device may recognize the family member is in the
home. These determinations may be compared to data received from
the mobile device indicating the mobile device is located outside
of the home. Such a determined incongruity may result in the mobile
device being determined to be operating anomalously.
[0084] In another example, a request may be provided to a device to
determine whether location related features of the device are
enabled. For example the request may include an instruction to
provide an indicator of whether a wireless location service is
enabled on the device or whether a Wi-Fi radio is enabled on the
device. Responses to such requests may be received and compared to
anomalous operating conditions such as conditions that the location
service is disabled or that the Wi-Fi radio is disabled when a
location operation only functions over the Wi-Fi network. If such a
conditions are satisfied, then the device may be determined to be
operating anomalously.
[0085] Anomalous operations may not be detectable to a family
member using the device because, for example, they involve a
background operations on the mobile device, the anomalously
operating mobile device is turned off or locked, the screen is
malfunctioning, the battery is discharged, or a network interface
is malfunctioning or network connectivity is otherwise lost.
Therefore, in some implementations, it may be beneficial to provide
notifications to the other mobile devices registered to the family
account of the anomalously operating device. In other
implementations, a notification may be provided to all devices
registered to the family account, including the device operating
anomalously.
[0086] In an implementation of this disclosure, a premises
management system may provide notifications to each mobile device
associated with a premises management system when a particular
mobile device associated with the premises management system is
determined to be operating anomalously. For example, FIG. 8 shows a
sequence diagram for providing notifications to devices associated
with a premises management system according to an implementation of
this disclosure. At 810, premises management system 700 may
transmit a request to mobile device 710. For example, the request
may include an instruction to transmit location data to the
premises management system. A threshold period of time may expire
after the request is provided. For example no response may be
received within nine minutes of transmitting the request. In
response to the expiration of this threshold period of time, at 820
a notification may be provided to each other mobile device 720, 730
registered with the family account. This notification may instruct
each other mobile device to display a push notification to the
interface of each mobile device that alerts the family member of
the anomalous operation of mobile device 710.
[0087] In another implementation of this disclosure, premises
management system may determine a mobile device is operating
anomalously based on a response from the anomalous device. For
example, FIG. 9 shows a sequence diagram for providing
notifications to devices associated with a premises management
system according to an implementation of this disclosure. At 910
premises management system 700 may provide a request to mobile
device 710 belonging to a family member of the family account. This
request may be, for example, for mobile device 710 to provide an
indicator of the state of an operation of the mobile device related
to location. For example the request may be for an indicator of
whether location services on the mobile device have been enabled or
to determine a location of the mobile device and provide an
indicator of that location. At 920, the mobile device 710 may
provide a response to premises management system 700. For example
the response may be an indicator of the operation, such as an
indicator that location services have not been enabled, or an
indicator of the location data that is the result of the location
determination operation.
[0088] Premises management system 700 may determine, based on the
response at 920, that mobile device 710 is operating anomalously.
Mobile device 710 may be operating anomalously if, for example, an
operation of mobile device 710, such as a location generation
operation of a location generation component of mobile device 710
is associated with an anomaly. For example, the premises management
system may compare the indicator included in the response to an
anomalous operating condition, such as the condition of location
services being disabled. A match or other correspondence between
the indicator of the operation received from mobile device 710 and
the anomalous operating condition may determine that the device is
operating anomalously. In general, determinations that operation of
a location generation component of a mobile computing device is
associated with an anomaly may be made in accordance with any of
the suitable techniques discussed herein, such as by the detection
on an anomaly as discussed with respect to FIGS. 1-6. In response
to this determination, at 930, premises management system 700 may
transmit a notice to each mobile device 720, 730 included in the
family account.
[0089] Additionally, in some implementations, responses such as at
920 may be received independent of a request from the premises
management system. For example, each mobile device in the family
account may periodically provide operation indicators, such as
location indicators to the premises management system. These
location indicators may be used by the premises management system
in a manner similar to the requested location indicators described
with respect to FIGS. 7-15.
[0090] In an implementation of this disclosure, it may be
determined that a mobile device may have stopped operating
anomalously and started operating normally. For example, FIG. 10
shows a sequence diagram for providing notifications to devices
associated with a premises management system according to an
implementation of this disclosure, where a notification may include
an indicator that a formerly anomalously operating device is now
operating normally. At 1010 premises management system 700 may
transmit a request to mobile device 710, and at 1020 premises
management system 700 may receive a response from mobile device
710. Premises management system 700 may determine that mobile
device 710 is operating anomalously and at 1030, premises
management system 700 may provide an indicator of mobile device
710's anomalous operation to each mobile device 720, 730 registered
to the family account. At a later time, at 1040, premises
management system 700 may provide a second request to mobile device
710. At 1050, mobile device 710 may provide a response to premises
management system 700, and based on this response, premises
management system 700 may determine that mobile device 710 is
operating normally. For example an indicator included in the
response at 1050 may not match any anomalous operating condition.
As a result, at 1060, premises management system 700 may send a
notice to family member mobile devices 720, 730 indicating mobile
device 710 is operating normally.
[0091] In implementations of this disclosure, a premises management
system may prevent the receipt of data from an anomalously
operating device. For example, FIG. 11 shows a procedure in
accordance with an implementation of this disclosure. At 1110, a
premises management system may send a request to a mobile device
registered with an account such as the family account to perform a
particular operation. For example, the request may be an
instruction that when executed by the mobile device, causes the
mobile device to determine its location. The mobile device may
perform the particular operation, and at 1120, the premises
management system may receive an indicator of the particular
operation. For example, the indicator may be the location
determined by the mobile device. In some implementations, the
particular operation may be to determine a location of the mobile
device multiple times within a configurable time period. For
example, the request may be to determine how many times the mobile
device has crossed a geofenced boundary in a five minute time
period. The received indicator may be that mobile device has
crossed the geofence boundary four times in a two minute
period.
[0092] At 1130 the premises management system may compare the
received indicator of the particular operation to an anomalous
operating condition associated with the particular operation. For
example, the anomalous operating condition may be crossing the
geofenced boundary at least three times in a threshold five minute
period of time. If the indicator is received one time in a five
minute period, then the premises management system may determine
that the received indicator does not match the anomalous operating
condition, and at 1180, the mobile device may be determined to be
operating normally. In general any number of indicators received or
threshold period of time may be predetermined, preconfigured, or
otherwise specified as is suitable for the purposes of the
disclosure and the context of applications implementing the subject
matter of this disclosure.
[0093] If the received indicator is four times in a two minute
period, then the premises management system may determine at 1140
that the received indicator matches or otherwise satisfies the
anomalous operating condition, and at 1150, the mobile device may
be determined to be operating anomalously. The premises management
system may then select mobile devices to receive a notification,
and may select one or more mobile devices that are registered with
the family account other than the mobile device operating
anomalously.
[0094] In some implementations, only mobile devices associated with
certain family members may be selected. For example, the parent's
mobile device 730 and her oldest daughter's mobile device 720 may
be selected because they may be configured within the family
account to receive notices of anomalous operation. The youngest
child's mobile device 710 may not be selected based on a
configuration for her account indicating not to receive a
notification. At 1160, the premises management system may provide
an indicator of the anomalously operating mobile device to the
selected mobile devices.
[0095] A 1170, in addition to or instead of providing notifications
to mobile devices, premises management system 1170 may prevent use,
by the premises management system, of data received from the
anomalously operating mobile device. For example, a procedure may
determine whether occupants of a home are home or away by
determining whether location data from mobile devices of a family
account for the home indicate locations within a geofence
surrounding the home. In response to receiving an indicator of the
anomalous performance of location operations by a mobile device
within the family account, the premises management system may
prevent the use of location data from the anomalous mobile device.
For example all procedures executing on the premises management
system my block or delete location data received from the anomalous
device. In some implementations, the anomalous mobile device may be
deleted from the family account, or data from the anomalous mobile
device may be "quarantined" from procedures executing on the
premises management system.
[0096] In some implementations, in addition to or instead of
requesting that a mobile device associated with a particular
account provide an indicator of a location, the mobile device may
automatically periodically determine location and provide an
indicator of the determined location to the premises management
system. For example, a particular device may be one of a set of one
or more devices registered or otherwise associated with a
particular account, such as a family account. The particular device
can periodically determine its location in accordance with a
schedule or location sampling rate. The location of the device may
be determined by a location generation component, such as a
location service, utilizing one or more of the location generation
techniques discussed herein, such as a WiFi-based techniques. Once
the location is determined, the mobile device may transmit the
location to the premises management system.
[0097] In an example, a computing device in communication with the
premises management system may receive the indicator of location of
the mobile device or may not receive an indicator. The computing
device may store instructions, that when executed by a processor of
the computing device, cause the processor to determine that the
location generation component of the mobile device is associated
with an anomaly. For example, the indicator may be received, but
the location may significantly deviate from historical information
about the location of the mobile device. This deviation may be
associated with the operation of the location generation component
being associated with an anomaly. In another example, no indicator
may be received. The indicator may normally be received on a
particular schedule or at a particular rate, and the absence of the
indicator may be inconsistent with this schedule or rate. Such
inconsistencies may be associated with the operation of the
location generation component being associated with an anomaly. In
general, any of the anomaly determination techniques discussed
herein, such as those discussed with respect to FIGS. 1-5, may be
employed to determine that the operation of the location generation
component is associated with an anomaly.
[0098] In response to a determination that the location generation
component is associated with an anomaly, according to an
implementation, a computing device in communication with the
premises management system may select a second mobile device from
among the set of one or more devices associated with the account.
In response to the selection, the computing device can provide a
notice or other communication of the anomaly to the selected mobile
device. For example, an alert may be transmitted to the selected
mobile device that displays on a user interface of the mobile
device, and indicates the original mobile device is operating
anomalously.
[0099] In implementations of this disclosure, notices may be
provided to other mobile devices or data from an anomalous mobile
device may be blocked based on an absence of a response from a
mobile device. For example, FIG. 12 shows a procedure in accordance
with an implementation of this disclosure. At 1210 a request may be
provided to a mobile device to perform a particular operation. At
1220 it may be determined whether a response to the request has
been received. If the response has not been received, then the
amount of time that has elapsed since providing may be determined
and compared to a threshold time period at 1240. If the threshold
time period has not expired, then the procedure may return to
determine whether a response has been received at 1220. If the
threshold time period has expired, then at 1250 it may be
determined that the mobile device is operating anomalously.
[0100] According to an implementation, notifications may be
provided to selected mobile devices at 1260 and/or data associated
with the anomalous operation may be blocked or otherwise prevented
from being used by a premises management system at 1270. For
example, a mobile device may be determined to be operating
anomalously, and its location may have triggered an operation of a
premises management system. For example, the mobile device may have
generated a location indicating the mobile device was within a
premises. This location may have trigger a low security state for a
security subsystem of the premises management system. However, the
location generation component of the mobile device may be operating
anomalously, such as may be determined in accordance with any of
the techniques described herein. In response to determining the
location generation component is operating anomalously, the
premises management system may prevent operation of the security
system in the low state. For example, the premises management
system may provide an instruction to the security system to enter a
medium or high state.
[0101] As shown in FIG. 12, if a response was received in response
to the request by premises management system to perform a
particular operation, then at 1230 it may be determined whether an
indicator of the particular operation received with the response
satisfies an anomalous operation condition. In some examples, an
anomalous operating condition may initially be satisfied but later
become unsatisfied. For example, the mobile computing device may
initially not respond within a threshold period of time, rate, or
schedule and thus satisfy an anomalous operating condition. At a
later time, the mobile device may begin to respond within the
threshold period of time, rate, or schedule. In response, the
premises management system may determine that the location
generation component of the mobile device is operating normally. As
a result, the computing device in communication with the premises
management system can permit the execution by the premise
management system of a non-functioning or otherwise prevented
operation, such as the security level of the security system. Thus,
for example, upon the determination that the location generation
component is not operating anomalously, the security system may be
permitted to change the security level to high.
[0102] Implementations of this disclosure may interface with
members of the user community to improve the determination of
anomalous operations. For example, as discussed above, a premises
management system may provide a notice of a determined anomaly to
one or more mobile devices. In addition to alerting the users of
the mobile devices, the notice may include instructions to generate
an interface on the mobile device prompting the respective user to
confirm whether the determined anomaly was accurate.
[0103] In an example, a determined anomaly may be any type of
anomaly discussed in this disclosures or otherwise suitable for the
purposes of this disclosure. For example, an anomaly may be
determined to be that a pattern of location indicators of the
mobile device deviates from a pattern of historical location
information for the mobile device. For example location indicators
of a particular mobile device may indicate the mobile device was
located a several different cities that are distant from a premises
associated with the mobile device. There may not have been any
intervening location indicators received between a location
indicator received at the premises and a later location indicator
received at a distant city. These indicators may be received at
night after 10:00 pm. Historical information may indicate that the
mobile device is most commonly located at the premises during this
time or that, if the mobile device travels, there are a series of
location indicators received as the mobile device travels away from
the premises. Based on this deviation, the premises management
system may determine that there is an anomalous operation.
[0104] The premises management system may provide notices to other
mobile devices associated with a linked account to inform those
users of the anomalously operating device. One or more of the
notified users may select, via an interface of their mobile device,
a prompt that denies that the operation was anomalous. For example,
the user of the anomalous device in the preceding example may be
known by other users to be on a road trip that night and traveling
with his mobile device primarily powered off in order to save
energy. A record may be generated by the premises management system
indicating that the prior determined anomalous operation is
associated with a user of an associated account selecting that the
anomaly was inaccurate. This record may be used by the premises
management system in the future to improve future anomaly
determinations, such as, for example, in accordance with the
machine learning techniques discussed below.
[0105] In some implementations, such as those discussed above with
respect to FIGS. 1-6, an application executing on a particular
mobile device may notify a user of the particular mobile device
that the location generation component of the particular mobile
device is associated with an anomaly. The anomaly may be any type
of anomaly discussed in this disclosure or suitable for the
purposes of this disclosure. For example, the anomaly may be a
deviation from historical information discussed above, a
misconfigured wireless radio of the particular mobile device, or
that an operating system of the particular mobile device is not
operating properly. A notice of the anomaly may be presented on the
particular device and the user may be provided the opportunity to
make a selection of whether a location generation operation
associated with the determined anomaly is accurate or inaccurate.
For example, the user may select whether the indicator of location
of the mobile device is accurate or inaccurate. In response to the
user's selection, the particular mobile device can generate a
record associating the determined anomaly and the user's selection
of accuracy or inaccuracy and provide the record to a remote
computing device in communication with the premises management
system.
[0106] In implementations of the disclosure, machine learning
techniques may be employed to determine anomalies. Any machine
learning technique may be employed that is suitable for the
purposes of this disclosure. Suitable machine learning techniques
may include linear regression, naive Bayes, logistic regression,
optimized logistic regression, and neural networks. Neural networks
may include a deep neural network that includes multiple neural
network layers. In some implementations, in addition or as
alternatives to a deep neural network, the neural network may
include one or more recurrent neural network layers such as long
short-term memory layers, one or more convolutional neural network
layers, or one or more local contrast normalization layers. Neural
networks, as described herein, may also have the architecture of a
convolutional, long short-term memory, fully connected deep neural
network. In some instances, various types of filters such as
infinite impulse response filters, linear predictive filters,
Kalman filters, or the like may be implemented in addition to or as
part of one or more of the neural network layers.
[0107] In implementations of the disclosure, one or more computing
devices in communication with a premises management system may
execute machine learning techniques to determine anomalies. For
example, a computing device may receive from a particular mobile
device, a record indicating that a prior determined anomaly is
associated with a selection by a user of the particular mobile
device indicating a prior indicator of the location of the
particular mobile device was accurate or inaccurate. The computing
device executing machine learning techniques may process the record
along with other data about the state of the particular computing
device, and/or other data aggregated from other mobile devices
associated with anomaly determinations to determine anomaly
criteria.
[0108] According to an implementation, anomaly criteria may
function as or define anomalous operating conditions as discussed
throughout this disclosure and serve as a basis for determining
anomalies. For example, satisfaction of anomaly criteria may
determine the existence of an anomaly.
[0109] As an example, a record indicating that a user confirmed
that a location indicator of the user's mobile device was
inaccurate when that location indicator was associated with an
anomaly may serve to increase a machine learning factor such as a
transition probability, node value, weighting, or similar
relationship when the record is being processed by machine learning
techniques to determine characteristics of the anomaly. Similarly a
user's contradiction of a location indicator as inaccurate may
serve to weaken a machine learning factor. Multiple records from
multiple mobile devices may be processed by machine learning
techniques in the aggregate to compare and identify the strength of
the relationship between characteristics of anomalies and accurate
or inaccurate location indicators. A set of the strongest
characteristics may be identified and serve as anomaly criteria for
the identification of future anomalies.
[0110] Machine learning techniques may be applied to a large
numbers of records of anomalies that have been verified or
contradicted by users. These records may include information such
as the state of the mobile device or the device behavior when the
anomaly was detected. By analyzing large volumes of records,
machine learning techniques may extract common characteristics
among devices that submitted reports. Characteristics or sets of
characteristics may be previously unrecognized as affecting the
functioning of location generation components. For example
characteristics may include certain protocols or configurations of
the mobile device or components with which the mobile device
interacts, such as routers, cellular access points, or operating
systems. These characteristics or sets of characteristics may be
grouped or classified as anomaly criteria.
[0111] In some implementations, anomaly criteria may define an
anomaly. For example anomaly criteria may include aspects of the
state of a mobile device such as whether one or more a wireless
radios are activated, how they are configured, the state of an
operating system executing on the mobile device, historical
location information for the mobile device, historical patterns of
location information for the mobile device, as well as any other
criteria suitable for the purposes of the disclosure. In some
implementations the determination that an operation of a location
generation component on a mobile device is associated with an
anomaly may be based on the anomaly criteria and thereby also based
on a received record that contributed to that anomaly criteria. For
example, if anomaly criteria associated with a particular anomaly
are substantially matched, then the anomaly may be determined to be
present and the operation of the location generation component may
be determined to be associated with the anomaly.
[0112] Determination of an anomaly based on anomaly criteria may
take place on one or more computing devices in communication with a
premises management system, or on a mobile device. For example a
mobile device may receive anomaly criteria determined by a machine
learning system based on a prior record provided by the mobile
device to the machine learning system. The mobile device may
execute instructions to determine whether an indicator of a
location of the mobile device is associated with an anomaly based
on the received anomaly criteria in accordance with the techniques
and procedures discussed throughout this disclosure.
[0113] FIG. 13 is a block diagram of an example of a premises
management device 1300 according to an implementation of the
disclosure. Premise management device 1300 can include a processor
1308, a memory 1310, a user interface (UI) 1304, a communications
interface 1306, an internal bus 1312, and one or more sensors 1302.
Premises management device 1300 may constitute or be a component of
a premises management system as discussed throughout this
disclosure. A person of ordinary skill in the art appreciates that
various components of the premises management device 1300 described
herein can include additional electrical circuit(s). Furthermore,
it is appreciated that many of the various components listed above
can be implemented on one or more integrated circuit (IC) chips.
For example, in one embodiment, a set of components can be
implemented in a single IC chip. In other embodiments, one or more
of respective components can be fabricated or implemented on
separate IC chips.
[0114] The sensor 1302 can be an environmental sensor, such as a
temperature sensor, smoke sensor, carbon monoxide sensor, motion
sensor, accelerometer, proximity sensor, passive infrared (PIR)
sensor, magnetic field sensor, radio frequency (RF) sensor, light
sensor, humidity sensor, pressure sensor, microphone, compass, or
any other environmental sensor that obtains or provides a
corresponding type of information about the environment in which
the premises management device 1300 is located.
[0115] The processor 1308 can be a central processing unit (CPU) or
other type of processor and can be communicably connected to the
other components to receive and analyze data obtained by the sensor
1302, can transmit messages or packets that control operation of
other components of the premises management device 1300 and/or
external devices, and can process communications between the
premises management device 1300 and other devices. The processor
1308 can execute instructions and/or computer executable components
stored on the memory 1310. Such computer executable components can
include, for example, a primary function component to control a
primary function of the premises management device 1300 related to
managing a premises, a communication component to locate and
communicate with other compatible premises management devices, a
computational component to process system related tasks, or any
combination thereof.
[0116] The memory 1310 or another memory in the premises management
device 1300 can also be communicably connected to receive and store
environmental data obtained by the sensor 1302. A communication
interface 1306 can function to transmit and receive data using a
wireless protocol, such as a WiFi.TM., Thread.RTM., or other
wireless interface, Ethernet.RTM. or other local network interface,
Bluetooth.RTM. or other radio interface, or the like and can
facilitate transmission and receipt of data by the premises
management device 1300 to and from other devices.
[0117] The user interface (UI) 1304 can provide information and/or
receive input from a user of the premises management system 204.
The UI 1304 can include, for example, a speaker to output an
audible sound when an event is detected by the premises management
device 1300. Alternatively or additionally, the UI 1304 can include
a light to be activated when an event is detected by the premises
management device 1300. The UI 1304 can be relatively minimal, such
as a liquid crystal display (LCD), light-emitting diode (LED)
display, or limited-output display, or it can be a full-featured
interface such as a touchscreen, keypad, or selection wheel with a
click-button mechanism to enter input.
[0118] Internal components of the premises management device 1300
can transmit and receive data to and from one another via an
internal bus 1312 or other mechanism. One or more components can be
implemented in a single physical arrangement, such as where
multiple components are implemented on a single integrated circuit.
Premises management devices 1300 can include other components,
and/or may not include all of the components illustrated.
[0119] The sensor 1302 can obtain data about the premises, and at
least some of the data can be used to implement the security
system. Through the bus 1312 and/or communication interface 1306,
sensor data can be transmitted to or accessible by other components
of the premises management system 204.
[0120] Generally, two or more sensors 1302 on one or more premises
management devices 1300 can generate data that can be coordinated
by the primary system processor to determine a system response
and/or infer a state of the environment. In one example, the
primary system processor of the system can infer a state of
intrusion based on data from entry detection sensors and motion
sensors and, based on the determined state, further determine
whether an unauthorized party is present and a location, within the
premises, of the unauthorized party.
[0121] In another example, an ambient light sensor in a room may
determine that the room is dark (e.g., less than 60 lux). A
microphone in the room may detect a sound above a set threshold,
such as 60 dB. The system processor may determine, based on the
data generated by both sensors, that it should activate one or more
lights in the room. In the event the processor only received data
from the ambient light sensor, the system may not have any basis to
alter the state of the lighting in the room. Similarly, if the
processor only received data from the microphone, the system may
lack sufficient data to determine whether activating the lights in
the room is necessary, for example, during the day the room may
already be bright or during the night the lights may already be on.
As another example, two or more sensors may communicate with one
another. Thus, data generated by multiple sensors simultaneously or
nearly simultaneously may be used to determine a state of an
environment and, based on the determined state, generate a
response.
[0122] As another example, a system may employ a magnetometer
affixed to a door jamb and a magnet affixed to the door. When the
door is closed, the magnetometer may detect the magnetic field
emanating from the magnet. If the door is opened, the increased
distance may cause the magnetic field near the magnetometer to be
too weak to be detected by the magnetometer. If the system is
activated, it may interpret such non-detection as the door being
ajar or open. In some configurations, a separate sensor or a sensor
integrated into one or more of the magnetometer and/or magnet may
be incorporated to provide data regarding the status of the door.
For example, an accelerometer and/or a compass may be affixed to
the door and indicate the status of the door and/or augment the
data provided by the magnetometer. A compass or similar sensor may
be used in conjunction with a magnet, such as to more precisely
determine a distance from the magnet, or it may be used alone and
provide environmental information based on the ambient magnetic
field, as with a conventional compass.
[0123] In some configurations, an accelerometer may be employed to
indicate how quickly the door is moving. For example, the door may
be lightly moving due to a breeze. This may be contrasted with a
rapid movement due to a person swinging the door open. The data
generated by the compass, accelerometer, and/or magnetometer may be
analyzed and/or provided to a central system such as a controller
device 1412 and/or remote system 1408 depicted in FIG. 14 below.
The data may be analyzed to learn a user behavior, an environment
state, and/or as a component of a smart home system. While the
above example is described in the context of a door, a person
having ordinary skill in the art will appreciate the applicability
of the disclosed subject matter to other implementations such as a
window, garage door, fireplace doors, vehicle windows/doors, faucet
positions (e.g., an outdoor spigot), a gate, seating position,
other openings, etc.
[0124] The data collected from one or more sensors may be used to
determine the physical status and/or occupancy status of a
premises, for example whether one or more family members are home
or away. For example, open/close sensors such as door sensors may
be used to determine that an unknown person has entered the
premises. The system may first determine that a person has entered
the premises due to sensors detecting a door opening and closing in
a time span previously determined to be consistent with a person
entering or leaving the premises. The system next may identify the
person as "unknown" due to the absence of a smartphone, key fob,
wearable device, or other device typically used to identify
occupants of the premises. Continuing the example, sensor data may
be received indicating that a valuable item within the premises has
been moved, or that a component of the smart home environment
associated with security functions such as a controller disclosed
herein, has been moved or damaged. Such sensor data may be
received, for example, from a sensor attached to or otherwise
associated with the valuable item, from the smart home component
itself, or from one or more other sensors within the premises. In
response, the system may generate an alert indicating that an
unknown person has entered the premises and/or that the item or
component has been moved or damaged. The system may further
determine that an occupant of the home is close by but not present
in the premises, for example based upon a Wi-Fi signal received
from the occupant's smartphone, but an absence of near-field or
other short-range communication from the same smartphone. In this
case, the system may be configured to send the alert to the
occupant's smartphone, such as via SMS, email, or other
communication. As another example, the system may determine that
the premises is already in an "away" state and that no occupants
are nearby or expected to return in the near future. In this case,
the system may be configured to send the alert to a local law
enforcement agency, such as via email, SMS, recorded phone call, or
the like.
[0125] Data generated by one or more sensors may indicate patterns
in the behavior of one or more users and/or an environment state
over time, and thus may be used to "learn" such characteristics.
For example, sequences of patterns of radiation may be collected by
a capture component of a device in a room of a premises and used as
a basis to learn object characteristics of a user, pets, furniture,
plants, and other objects in the room. These object characteristics
may make up a room profile of the room and may be used to make
determinations about objects detected in the room.
[0126] In another example, data generated by an ambient light
sensor in a room of a house and the time of day may be stored in a
local or remote storage medium with the permission of an end user.
A processor in communication with the storage medium may compute a
behavior based on the data generated by the light sensor. The light
sensor data may indicate that the amount of light detected
increases until an approximate time or time period, such as 3:30
pm, and then declines until another approximate time or time
period, such as 5:30 pm, at which point there is an abrupt increase
in the amount of light detected. In many cases, the amount of light
detected after the second time period may be either below a dark
level of light (e.g., under or equal to 60 lux) or bright (e.g.,
equal to or above 400 lux). In this example, the data may indicate
that after 5:30 pm, an occupant is turning on/off a light as the
occupant of the room in which the sensor is located enters/leaves
the room. At other times, the light sensor data may indicate that
no lights are turned on/off in the room. The system, therefore, may
learn occupants' patterns of turning on and off lights, and may
generate a response to the learned behavior. For example, at 5:30
pm, a smart home environment or other sensor network may
automatically activate the lights in the room if it detects an
occupant in proximity to the home. In some embodiments, such
behavior patterns may be verified using other sensors. Continuing
the example, user behavior regarding specific lights may be
verified and/or further refined based upon states of, or data
gathered by, smart switches, outlets, lamps, and the like.
[0127] Such learning behavior may be implemented in accordance with
the techniques disclosed herein. For example, a system of smart
home environment as disclosed herein may be configured to learn
appropriate notices to generate or other actions to take in
response to a determination that a notice should be generated,
and/or appropriate recipients of a particular notice or type of
notice. As a specific example, a system of smart home environment
may determine that after a notice has been sent to a first occupant
of a premises indicating that a window in a room has been left
open, a second occupant is always detected in the room within a
threshold time period, and the window is closed shortly thereafter.
After making such a determination, in future occurrences the notice
may be sent to the second occupant or to both occupants for the
purposes of improving the efficacy of the notice. In an
implementation, such learned behaviors may be reviewed, overridden,
modified, or the like by a user of the system, such as via a
computer-provided interface to as disclosed herein
[0128] FIG. 14 is a block diagram of an example of a premises
management system 1400 according to an implementation of the
disclosure. The premises management system 1400 can include
security system features. The premises management system 1400 can
be implemented over any suitable wired and/or wireless
communication networks. One or more premises management devices,
i.e., sensors 1402, 1404, 1406, and one or more controller devices
1412 can communicate via a local network 1414, such as a WiFi.TM.
or other suitable network, with each other. The network 1414 can
include a mesh-type network such as a Thread.RTM. network, which
can provide network architecture and/or protocols for devices to
communicate with one another. An authorized party can therefore
interact with the premises management system 1400, for example,
using the controller device 1412, which can communicate with the
rest of the premises management system 1400 via the network
1414.
[0129] The controller device 1412 and/or one or more of the sensors
1402, 1404, 1406, can be configured to implement a primary system
processor 1410. The primary system processor 1410 can, for example,
receive, aggregate, and/or analyze environmental information
received from the sensors 1402, 1404, 1406, and the controller
device 1412. Furthermore, a portion or percentage of the primary
system processor 1410 can be implemented in a remote system 1408,
such as a cloud-based reporting and/or analysis system. The remote
system 1408 can, for example, independently aggregate data from
multiple locations, provide instruction, software updates, and/or
aggregated data to a controller 1412, primary system processor
1410, and/or sensors 1402, 1404, 1406.
[0130] The sensors 1402, 1404, 1406, can be disposed locally to one
another, such as within a single dwelling, office space, building,
room, or the like, or they may be disposed remote from each other,
such as at various locations around a wide perimeter of a premises.
In some embodiments, sensors 1402, 1404, 1406, can communicate
directly with one or more remote systems 1408. The remote system
1408 can, for example, aggregate data from multiple locations,
provide instruction, software updates, and/or aggregated data to
the primary system processor 1410, controller device 1412, and/or
sensors 1402, 1404, 1406. Additionally, remote system 1408 can
refer to a system or subsystem that is a part of a third party
monitoring service or a law enforcement service.
[0131] The premises management system illustrated in FIG. 14 can be
a part of a smart-home environment, which can include a structure,
such as a house, office building, garage, mobile home, or the like.
The devices of the smart home environment, such as the sensors
1402, 1404, 1406, and the network 1414 can be integrated into a
smart-home environment that does not include an entire structure,
such as a single unit in an apartment building, condominium
building, or office building.
[0132] The smart home environment can control and/or be coupled to
devices outside of the structure. For example, one or more of the
sensors 1402, 1404 can be located outside the structure at one or
more distances from the structure (e.g., sensors 1402, 1404 can be
disposed outside the structure, at points along a land perimeter on
which the structure is located, or the like. One or more of the
devices in the smart home environment may not be physically within
the structure. For example, the controller 1412, which can receive
input from the sensors 1402, 1404, can be located outside of the
structure.
[0133] The structure of the smart-home environment can include a
plurality of rooms, separated at least partly from each other via
walls. The walls can include interior walls or exterior walls. Each
room can further include a floor and a ceiling. Devices of the
smart-home environment, such as the sensors 1402, 1404, can be
mounted on, integrated with, and/or supported by a wall, floor, or
ceiling of the structure.
[0134] The controller device 1412 can be a general or
special-purpose controller. For example, one type of controller
device 1412 can be a general-purpose computing device running one
or more applications that collect and analyze data from one or more
sensors 1402, 1404, 1406 within the home. In this case, the
controller device 1412 can be implemented using, for example, a
mobile computing device such as a mobile phone, a tablet computer,
a laptop computer, a personal data assistant, or wearable
technology. Another example of a controller device 1412 can be a
special-purpose controller that is dedicated to a subset of
functions, such as a security controller that collects, analyzes
and provides access to sensor data primarily or exclusively as it
relates to various security considerations for a premises. The
controller device 1412 can be located locally with respect to the
sensors 1402, 1404, 1406 with which it can communicate and from
which it can obtain sensor data, such as in the case where it is
positioned within a home that includes a home automation and/or
sensor network. Alternatively or additionally, controller device
1412 can be remote from the sensors 1402, 1404, 1406, such as where
the controller device 1412 is implemented as a cloud-based system
that can communicate with multiple sensors 1402, 1404, 1406, which
can be located at multiple locations and can be local or remote
with respect to one another.
[0135] Sensors 1402, 1404, 1406 can communicate with each other,
the controller device 1412, and the primary system processor 1410
within a private, secure, local communication network that can be
implemented wired or wirelessly, and/or a sensor-specific network
through which sensors 1402, 1404, 1406 can communicate with one
another and/or with dedicated other devices. Alternatively, as
illustrated in FIG. 14, one or more sensors 1402, 1404, 1406 can
communicate via a common local network 1414, such as a Wi-Fi.TM.,
Thread.RTM., or other suitable network, with each other, and/or
with the controller 1412 and primary system processor 1410.
Alternatively or additionally, sensors 1402, 1404, 1406 can
communicate directly with a remote system 1408.
[0136] The communication and network protocols used by the devices
communicatively coupled to the network 1414 may provide secure
communications, minimize the amount of power used (i.e., be power
efficient), and support a wide variety of devices and/or products
in a home, such as appliances, access control, climate control,
energy management, lighting, safety, and security. For example, the
protocols supported by the network and the devices connected
thereto may have an open protocol which may carry IPv6
natively.
[0137] A Thread.RTM. network, such as network 1414, may be easy to
set up and secure to use. The network 1414 may use an
authentication scheme, such as AES (Advanced Encryption Standard)
encryption or the like, to reduce and/or minimize security holes
that exist in other wireless protocols. The Thread network may be
scalable to connect devices (e.g., 2, 5, 10, 20, 50, 100, 310, 200,
or more devices) into a single network supporting multiple hops
(e.g., so as to provide communications between devices when one or
more nodes of the network is not operating normally). The network
1414, which may be a Thread network, may provide security at the
network and application layers. One or more devices communicatively
coupled to the network 1414 (e.g., controller device 1412, remote
system 1408, and the like) may store product install codes to
ensure only authorized devices can join the network 1414. One or
more operations and communications of network 1414 may use
cryptography, such as public-key cryptography.
[0138] The devices communicatively coupled to the network 1414 of
the smart home environment disclosed herein may have low power
consumption and/or reduced power consumption. That is, devices
efficiently communicate to with one another and operate to provide
functionality to the user, where the devices may have reduced
battery size and increased battery lifetimes over conventional
devices. The devices may include sleep modes to increase battery
life and reduce power requirements. For example, communications
between devices coupled to the network 1414 may use the
power-efficient IEEE 802.15.4 MAC/PHY protocol. In embodiments of
the disclosed subject matter, short messaging between devices on
the network 1414 may conserve bandwidth and power. The routing
protocol of the network 1414 may reduce network overhead and
latency. The communication interfaces of the devices coupled to the
smart home environment may include wireless system-on-chips to
support the low-power, secure, stable, and/or scalable
communications network 1414.
[0139] The smart-home environment, including the sensor network
shown in FIG. 14, can include a plurality of premises management
devices, including intelligent, multi-sensing, network-connected
devices that can integrate seamlessly with each other and/or with a
central server or a cloud-computing system (e.g., device controller
1412 and/or remote system 1408) to provide home-security and
smart-home features. Such devices can include one or more
intelligent, multi-sensing, network-connected thermostats (e.g.,
"smart thermostats"), one or more intelligent, network-connected,
multi-sensing hazard detection units (e.g., "smart hazard
detectors"), one or more intelligent, multi-sensing,
network-connected entryway interface devices (e.g., "smart
doorbells"), or any combination thereof. The smart hazard
detectors, smart thermostats, and smart doorbells can be, for
example, the sensors 1402, 1404, 1406 illustrated in FIG. 14. These
premises management devices can be used by the security system, but
can also have separate, primary functions.
[0140] For example, a smart thermostat can detect ambient climate
characteristics (e.g., temperature and/or humidity) and can
accordingly control a HVAC system of the structure. For example,
the ambient climate characteristics can be detected by sensors
1402, 1404, 1406 illustrated in FIG. 14, and the controller 1412
can control the HVAC system (not illustrated) of the structure.
However, unusual changes in temperature of a given room can also
provide data that can supplement a determination of whether a
situation is a security concern, for example, detecting a rapid
drop in temperature in a given room due to a broken in window.
[0141] As another example, a smart hazard detector can detect the
presence of a hazardous substance or a substance indicative of a
hazardous substance (e.g., smoke, fire, or carbon monoxide). For
example, smoke, fire, and/or carbon monoxide can be detected by
sensors 1402, 1404, 1406 illustrated in FIG. 14, and the controller
1412 can control an alarm system to provide a visual and/or audible
alarm to the user of the smart-home environment. However, the
speaker of the hazard detector can also be used to announce
security related messages.
[0142] As another example, a smart doorbell can control doorbell
functionality, detect a person's approach to or departure from a
location (e.g., an outer door to the structure), and announce a
person's approach or departure from the structure via an audible
and/or visual message that can be output by a speaker and/or a
display coupled to, for example, the controller 1412. However, the
detection of an approach of an unknown party can provide data to
the security system to supplement determining whether the presence
of the unknown party is a security concern.
[0143] In some embodiments, the smart home environment implemented
over the network 1414 shown in FIG. 14 may include one or more
intelligent, multi-sensing, network-connected wall switches (e.g.,
"smart wall switches"), one or more intelligent, multi-sensing,
network-connected wall plug interfaces (e.g., "smart wall plugs").
The smart wall switches and/or smart wall plugs may be or include
one or more of the sensors 1402 and 1404 shown in FIG. 14. A smart
wall switch may detect ambient lighting conditions, and control a
power and/or dim state of one or more lights. For example, a sensor
such as sensors 1402 and 1404, may detect ambient lighting
conditions, and a device such as the controller device 1412 may
control the power to one or more lights (not shown) in the smart
home environment. Smart wall switches may also control a power
state or speed of a fan, such as a ceiling fan. For example,
sensors 1402 and 1404 may detect the power and/or speed of a fan,
and the controller device 1412 may adjust the power and/or speed of
the fan, accordingly. Smart wall plugs may control supply of power
to one or more wall plugs (e.g., such that power is not supplied to
the plug if nobody is detected to be within the smart home
environment). For example, one of the smart wall plugs may control
supply of power to a lamp (not shown).
[0144] A smart-home environment can include one or more
intelligent, multi-sensing, network-connected entry detectors
(e.g., "smart entry detectors") that can be specifically designed
to function as part of a security subsystem. Such detectors can be
or can include one or more of the sensors 1402, 1404, 1406
illustrated in FIG. 14. The smart entry detectors can be disposed
at one or more windows, doors, and other entry points of the
smart-home environment to detect when a window, door, or other
entry point is opened, broken, breached, and/or compromised. The
smart entry detectors can generate a corresponding signal to be
provided to the controller 1412, primary system processor 1410,
and/or the remote system 1408 when a window or door is opened,
closed, breached, and/or compromised. In some embodiments of the
security system, the alarm, which can be included with controller
device 1412 and/or coupled to the network 1414, may not arm unless
all smart entry detectors (e.g., sensors 1402, 1404, 1406) indicate
that all doors, windows, entryways, and the like are closed and/or
that all smart entry detectors are armed.
[0145] The smart home environment implemented over the network
shown in FIG. 14 can include one or more intelligent,
multi-sensing, network-connected doorknobs (e.g., "smart
doorknob"). For example, the sensors 1402 and 1404 may be coupled
to a doorknob of a door (e.g., doorknobs located on external doors
of the structure of the smart home environment). However, it should
be appreciated that smart doorknobs can be provided on external
and/or internal doors of the smart home environment.
[0146] The smart thermostats, the smart hazard detectors, the smart
doorbells, the smart wall switches, the smart wall plugs, the smart
entry detectors, the smart doorknobs, the keypads, and other
devices of a smart home environment (e.g., as illustrated as
sensors 1402 and 1404 of FIG. 14) can be communicatively coupled to
each other via the network 1414, and to the controller 1412 and/or
remote system 1408 to provide security, safety, and/or comfort for
the smart home environment. Alternatively or in addition, each of
the devices of the smart home environment may provide data that can
be used to determine an occupancy and/or physical status of a
premises, as well as data that may be used to determine an
appropriate recipient of a notification, as previously disclosed
herein.
[0147] One or more users can control one or more of the
network-connected smart devices in the smart-home environment using
a network-connected computer or portable electronic device. In some
examples, some or all of the users (e.g., individuals who live in
the home) can register their mobile device, token and/or key fobs
with the smart-home environment (e.g., with the controller 1412).
Such registration can be made at a central server (e.g., the
controller 1412 and/or the remote system 14014) to authenticate the
user and/or the electronic device as being associated with the
smart-home environment, and to provide permission to the user to
use the electronic device to control the network-connected smart
devices and the security system of the smart-home environment. A
user can use their registered electronic device to remotely control
the network-connected smart devices and security system of the
smart-home environment, such as when the occupant is at work or on
vacation. The user can also use their registered electronic device
to control the network-connected smart devices when the user is
located inside the smart-home environment.
[0148] As an alternative to or in addition to registering
electronic devices, the smart-home environment can make inferences
about which individuals live in the home and are therefore users
and which electronic devices are associated with those individuals.
As such, the smart-home environment can learn who is a user (e.g.,
an authorized user) and permit the electronic devices associated
with those individuals to control the network-connected smart
devices of the smart-home environment (e.g., devices
communicatively coupled to the network 1414) including, in some
embodiments, sensors used by or within the smart-home environment.
Various types of notices and other information can be provided to
users via messages sent to one or more user electronic devices. For
example, the messages can be sent via e-mail, short message service
(SMS), multimedia messaging service (MIMS), unstructured
supplementary service data (USSD), as well as any other type of
messaging services and/or communication protocols. As previously
described, such notices may be generated in response to specific
determinations of the occupancy and/or physical status of a
premises, or they may be sent for other reasons as disclosed
herein.
[0149] FIG. 15 is a block diagram of an example of a computing
device 1500 suitable for implementing certain devices illustrated
in FIGS. 1 through 14. The computing device 1500 can be used to
implement, for example, the controller device 1412 or a premises
management device including sensors as described above. The
computing device 1500 can be constructed as a custom-designed
device or can be, for example, a special-purpose desktop computer,
laptop computer, or mobile computing device such as a smart phone,
tablet, personal data assistant, wearable technology, or the
like.
[0150] The computing device 1500 can include a bus 1502 that
interconnects major components of the computing device 1500. Such
components can include a central processor 1504; a memory 1506
(such as Random Access Memory (RAM), Read-Only Memory (ROM), flash
RAM, or the like), a sensor 1508 (which can include one or more
sensors), a display 1510 (such as a display screen), an input
interface 1512 (which can include one or more input devices such as
a keyboard, mouse, keypad, touch pad, turn-wheel, and the like), a
fixed storage 1514 (such as a hard drive, flash storage, and the
like), a removable media component 1516 (operable to control and
receive a solid-state memory device, an optical disk, a flash
drive, and the like), a network interface 1518 (operable to
communicate with one or more remote devices via a suitable network
connection), and a speaker 1520 (to output an audible
communication). In some embodiments the input interface 1512 and
the display 1510 can be combined, such as in the form of a touch
screen.
[0151] The bus 1502 can allow data communication between the
central processor 1504 and one or more memory components 1514,
1516, which can include RAM, ROM, or other memory. Applications
resident with the computing device 1500 generally can be stored on
and accessed via a computer readable storage medium.
[0152] The fixed storage 1514 can be integral with the computing
device 1500 or can be separate and accessed through other
interfaces. The network interface 1518 can provide a direct
connection to the premises management system and/or a remote server
via a wired or wireless connection. The network interface 1518 can
provide such connection using any suitable technique and protocol,
including digital cellular telephone, WiFi.TM., Thread.RTM.,
Bluetooth.RTM., near field communications (NFC), and the like. For
example, the network interface 1518 can allow the computing device
1500 to communicate with other components of the premises
management system or other computers via one or more local,
wide-area, or other communication networks.
[0153] In situations in which the systems discussed here collect
personal information about users, or may make use of personal
information, the users may be provided with an opportunity to
control whether programs or features collect user information
(e.g., information about a user's social network, social actions or
activities, profession, a user's preferences, or a user's current
location), or to control whether and/or how to receive content from
the content server that may be more relevant to the user. In
addition, certain data may be treated in one or more ways before it
is stored or used, so that personally identifiable information is
removed. For example, specific information about a user's residence
may be treated so that no personally identifiable information can
be determined for the user, or a user's geographic location may be
generalized where location information is obtained (such as to a
city, ZIP code, or state level), so that a particular location of a
user cannot be determined. As another example, systems disclosed
herein may allow a user to restrict the information collected by
those systems to applications specific to the user, such as by
disabling or limiting the extent to which such information is
aggregated or used in analysis with other information from other
users. Thus, the user may have control over how information is
collected about the user and used by a system as disclosed
herein.
[0154] The foregoing description, for purpose of explanation, has
been described with reference to specific embodiments. However, the
illustrative discussions above are not intended to be exhaustive or
to limit embodiments of the disclosed subject matter to the precise
forms disclosed. Many modifications and variations are possible in
view of the above teachings. The embodiments were chosen and
described in order to explain the principles of embodiments of the
disclosed subject matter and their practical applications, to
thereby enable others skilled in the art to utilize those
embodiments as well as various embodiments with various
modifications as may be suited to the particular use
contemplated.
* * * * *