U.S. patent application number 15/362581 was filed with the patent office on 2018-03-01 for methods, devices, and systems for determining an estimated time of departure and arrival based on information associated with the destination.
The applicant listed for this patent is Natnael S. Berhe, Tamerat S. Berhe, Bennett Jackson. Invention is credited to Natnael S. Berhe, Tamerat S. Berhe, Bennett Jackson.
Application Number | 20180058872 15/362581 |
Document ID | / |
Family ID | 61225746 |
Filed Date | 2018-03-01 |
United States Patent
Application |
20180058872 |
Kind Code |
A1 |
Berhe; Tamerat S. ; et
al. |
March 1, 2018 |
METHODS, DEVICES, AND SYSTEMS FOR DETERMINING AN ESTIMATED TIME OF
DEPARTURE AND ARRIVAL BASED ON INFORMATION ASSOCIATED WITH THE
DESTINATION
Abstract
Systems, devices, and methods for transmitting a selected route
of travel associated with a user equipment to allow the user of the
user equipment to arrive at the destination location on time, where
the route is based on a determined departure time for a
predetermined arrival time at a selected destination location.
Additionally, the determination is based on the current location of
the user equipment and real-time data pertaining to the selected
destination location, where the real-time data comprises detected
changes in surrounding environments at the selected destination
location.
Inventors: |
Berhe; Tamerat S.; (Loma
Linda, CA) ; Jackson; Bennett; (East Rutherford,
NJ) ; Berhe; Natnael S.; (Loma, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Berhe; Tamerat S.
Jackson; Bennett
Berhe; Natnael S. |
Loma Linda
East Rutherford
Loma |
CA
NJ
CA |
US
US
US |
|
|
Family ID: |
61225746 |
Appl. No.: |
15/362581 |
Filed: |
November 28, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62378912 |
Aug 24, 2016 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01C 21/3492 20130101;
G01C 21/3626 20130101; H04L 67/26 20130101; G06Q 50/30
20130101 |
International
Class: |
G01C 21/34 20060101
G01C021/34; H04L 29/08 20060101 H04L029/08; G01C 21/36 20060101
G01C021/36 |
Claims
1. A device comprising: a processor and addressable memory, the
addressable memory comprising a set of one or more rules, wherein
the device is in communication with a plurality of detection
equipment embedded in a set of line posts and having a transmitter,
and a user equipment having a processor and addressable memory,
wherein the processor of the device is configured to: receive, from
the plurality of detection equipment at a selected destination
location, real-time data pertaining to the selected destination
location requiring a traversal time to traverse a path at the
selected destination to arrive at a specified area within the
selected destination location, wherein the real-time data comprises
detected changes in surrounding environments at the selected
destination location to determine a length of local traversal time
within the selected destination location, the determination based
on the plurality of detection equipment embedded in the set of line
posts reading line data to monitor the traversal time; select a
route of travel from a departure location to the selected
destination location, based on live traffic info associated with
the selected departure location to the destination location, and
the live traffic info being received as real-time data; determine a
departure time for a predetermined arrival time at the specified
area within the selected destination location, wherein the
determination is based on the selected route of travel from the
selected departure location to the selected destination location,
and the determined length of local traversal time within the
selected destination location; and transmit, to the user equipment,
the determined departure time for the predetermined arrival time
and the selected route of travel associated with the user
equipment, thereby allowing the user of the user equipment to
depart from the selected departure location at a specified time in
order to arrive at the selected destination location at the
predetermined arrival time.
2. The device of claim 1 wherein the device is further configured
to determine a departure time for a predetermined arrival time
based on prediction data associated with the selected destination
location.
3. The device of claim 2 wherein the prediction data comprises
previously collected real-time data and is received by the device
on a continual basis.
4. The device of claim 3 wherein the real-time data and the
previously collected real-time data are length of traversal time
information related to how fast a line is moving at the specified
area within the selected destination location and at what rate the
line was growing at the specified area within the selected
destination location.
5. The device of claim 4 wherein the real-time data is traversal
information for the selected destination location and wherein the
prediction data is traversal information previously collected for
the selected destination location.
6. The device of claim 1 wherein the real-time data is collected
from a plurality of other user equipment present at the selected
destination location showing a rate of movement in traversing the
path at the selected destination location.
7. The device of claim 1 wherein the plurality of detection
equipment are a set of one or more sensors.
8. The device of claim 7 wherein the detected changes in
surrounding environments at the selected destination location is
based on data received from the set of one or more sensors.
9. The device of claim 8 wherein the detected changes in
surrounding environments at the selected destination location is
further based on a flow of movement tracked by the set of one or
more sensors for a group of line posts within the specified
area.
10. The device of claim 9 wherein the device is further configured
to determine line wait time information via the line data
associated with a scaling factor.
11. The device of claim 10 wherein the line wait time information
is further based on historical information associated with the
specified area, the historical information comprising at least one
of: number of staff working during that time, how fast the
particular staff works, and how crowded the lines are during that
time.
12. A method comprising: receiving, by a computing device
comprising a processor and addressable memory, from a plurality of
detection equipment embedded in a set of line posts, real-time data
pertaining to a selected destination location requiring a traversal
time to traverse a path at the selected destination to arrive at a
specified area within the selected destination location, wherein
the real-time data comprises detected changes in surrounding
environments at the selected destination location to determine a
length of local traversal time within the selected destination
location, the determination based on the plurality of detection
equipment embedded in the set of line posts reading line data to
monitor the traversal time; selecting, by the computing device, a
route of travel from a selected departure location to the selected
destination location, based on live traffic info associated with
the selected departure location, and the live traffic info being
received as real-time data; determining, by the computing device, a
departure time for a predetermined arrival time at the specified
area within the selected destination location, wherein the
determination is based on the selected route of travel from the
selected departure location to the selected destination location,
and to the selected destination location, and the determined length
of local traversal time within the selected destination location;
and transmitting, by the computing device to the user equipment,
the determined departure time for the predetermined arrival time
and the selected route of travel associated with the user
equipment, thereby allowing the user of the user equipment to
depart from the selected departure location at a specified time in
order to arrive at the selected destination location at the
predetermined arrival time.
13. The method of claim 12 wherein determining a departure time for
a predetermined arrival time is further based on prediction data
associated with the selected destination location.
14. The method of claim 13 wherein the prediction data comprises
previously collected real-time data and is received by the
computing device on a continual basis.
15. The method of claim 14 wherein the real-time data and the
previously collected real-time data are length of traversal time
information related to how fast a line is moving at the specified
area within the selected destination location and at what rate the
line was growing at the specified area within the selected
destination location.
16. The device of claim 15 wherein the real-time data is traversal
information for the selected destination location and wherein the
prediction data is traversal information previously collected for
the selected destination location.
17. A system comprising a computing device comprising a processor
and addressable memory, a user equipment, and a plurality of
detection equipment embedded in a set of line posts and having a
transmitter and a user equipment having a processor and addressable
memory; wherein the plurality of detection equipment embedded in
the set of line posts are configured to: send real-time data
pertaining to a selected destination location, wherein the
real-time data comprises detected changes in surrounding
environments at the selected destination location to determine a
length of local traversal time within the selected destination
location, the determination based on the plurality of detection
equipment embedded in the set of line posts reading line data to
monitor the traversal time; wherein the computing device is
configured to: receive, from the plurality of detection equipment,
real-time data pertaining to a selected destination location,
wherein the real-time data comprises detected changes in
surrounding environments at the selected destination location
associated with length of traversal time; select a route of travel
from a departure location to the selected destination location,
based on live traffic info associated with a selected departure
location, and live traffic info associated with the selected
departure location to the destination location, and the live
traffic info being received as real-time data; determine a
departure time for a predetermined arrival time at the specified
area within the selected destination location, wherein the
determination is based on the selected route of travel from the
selected departure location to the selected destination location,
and the determined length of local traversal time within the
selected destination location; and transmit, to the user equipment,
the determined departure time for the predetermined arrival time
and the selected route of travel associated with the user
equipment; and wherein the user equipment is configured to:
receive, from the computing device via a push notification, the
determined departure time for the predetermined arrival time and
the selected route of travel associated with the user equipment,
thereby allowing the user of the user equipment to depart from the
selected departure location at a specified time in order to arrive
at the selected destination location at the predetermined arrival
time.
18. The system of claim 17 wherein the computing device is further
configured to determine a departure time for a predetermined
arrival time based on prediction data associated with the selected
destination location.
19. The system of claim 18 wherein the prediction data comprises
previously collected real-time data and is received by the
computing device on a continual basis from the plurality of
detection equipment.
20. The system of claim 19 wherein the real-time data and the
previously collected real-time data are length of traversal time
information related to how fast a line is moving and at what rate
the line was growing, wherein the real-time data is traversal
information for the selected destination location and wherein the
prediction data is traversal information previously collected for
the selected destination location.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to and benefit of
Provisional Patent Application No. 62/378,912 filed Aug. 24, 2016,
which is hereby incorporated by reference for all purposes.
TECHNICAL FIELD OF ENDEAVOR
[0002] The present application relates to the field of
transportation and technology associated with determining wait
times at transportation facilities. More particularly, to
determining an estimated time of departure from a specified
location in order to arrive at a destination, based on a set of
information associated with the destination.
BACKGROUND
[0003] Currently, travelers and consumers are not privy to real
time information related to wait times at different lines or queues
in order to accomplish their travel plans on a timely fashion. A
traveler or user is not able to anticipate travel time to, for
example, an airport, and wait times at lines at the exemplary
airport. Methods and devices for providing information related to
the travel time to the destination is currently present, however,
potential wait time before clearing a waiting line and hence
arriving at the destination transportation facility is lacking. For
example, flights are often missed by misjudging the time in which
it will take a traveler to get (a) to the airport and/or (b) how
long, once at the airport, it will take the traveler to make it
through the check-in and TSA/Security lines.
SUMMARY
[0004] Embodiments may include methods, systems, and devices where,
for example, a device embodiment may include a processor and
addressable memory, the addressable memory comprising a set of one
or more rules, where the device may be in communication with a
plurality of detection equipment having a transmitter and a user
equipment having a processor and addressable memory. Additionally,
the processor of the device may be configured to: receive, from the
plurality of detection equipment, real-time data pertaining to a
selected destination location, where the real-time data may
comprise detected changes in surrounding environments at the
selected destination location associated with length of traversal
time; select a route of travel based on the received real-time data
pertaining to the selected destination location, live traffic info
associated with a selected departure location, and live traffic
info associated with the selected destination location; determine a
departure time for a predetermined arrival time at the selected
destination location, the determination based on the selected route
of travel, the selected departure location, and the selected
destination location; and transmit, to the user equipment, the
determined departure time for the predetermined arrival time and
the selected route of travel associated with the user equipment,
thereby allowing the user of the user equipment to depart from the
selected departure location at a specified time in order to arrive
at the selected destination location at the predetermined arrival
time.
[0005] The device embodiment may further be configured to determine
a departure time for a predetermined arrival time based on
prediction data associated with the selected destination location,
where the prediction data comprises previously collected real-time
data and is received by the device on a continual basis.
Optionally, the real-time data and the previously collected
real-time data may be length of traversal time information related
to how fast a line is moving and at what rate the line was growing.
Additionally, the real-time data may be traversal information for
the selected destination location and the prediction data may be
traversal information previously collected for the selected
destination location.
[0006] In another device embodiment, the real-time data may be
collected from a plurality of other user equipment present at the
selected destination location. Additionally, the plurality of
detection equipment may be a set of one or more sensors where the
detected changes in surrounding environments at the selected
destination location may be based on data received from the set of
one or more sensors and the detected changes in surrounding
environments at the selected destination location may be further
based on a flow of movement within a specified area. Optionally,
the device may be further configured to determine line wait time
information based on the flow of movement within the specified area
where the line wait time information may be further based on
historical information associated with the specified area.
[0007] Embodiments include methods, systems, and devices where, for
example a method embodiment may include, not necessarily in this
order, the steps of: (a) receiving, by a computing device
comprising a processor and addressable memory, from a plurality of
detection equipment, real-time data pertaining to a selected
destination location, where the real-time data may comprise
detected changes in surrounding environments at the selected
destination location associated with length of traversal time; (b)
selecting, by the computing device, a route of travel based on the
received real-time data pertaining to the selected destination
location, live traffic info associated with a selected departure
location, and live traffic info associated with the selected
destination location; (c) determining, by the computing device, a
departure time for a predetermined arrival time at the selected
destination location, the determination based on the selected route
of travel, the selected departure location, and the selected
destination location; and (d) transmitting, by the computing device
to the user equipment, the determined departure time for the
predetermined arrival time and the selected route of travel
associated with the user equipment, thereby allowing the user of
the user equipment to depart from the selected departure location
at a specified time in order to arrive at the selected destination
location at the predetermined arrival time.
[0008] Additionally, the method embodiment may determine a
departure time for a predetermined arrival time further based on
prediction data associated with the selected destination location,
where the prediction data may comprise previously collected
real-time data and may be received by the computing device on a
continual basis. Additionally, the real-time data and the
previously collected real-time data may be length of traversal time
information related to how fast a line is moving and at what rate
the line was growing. Optionally, the real-time data may be
traversal information for the selected destination location and the
prediction data may be traversal information previously collected
for the selected destination location.
[0009] Other embodiments include methods, systems, and devices
where, for example a system embodiment may include: (i) a computing
device comprising a processor and addressable memory, (ii) a user
equipment, and (iii) a plurality of detection equipment having a
transmitter and a user equipment having a processor and addressable
memory; where the plurality of detection equipment may be
configured to: send real-time data pertaining to a selected
destination location, where the real-time data comprises detected
changes in surrounding environments at the selected destination
location associated with length of traversal time; where the
computing device may be configured to: (a) receive, from the
plurality of detection equipment, real-time data pertaining to a
selected destination location, where the real-time data comprises
detected changes in surrounding environments at the selected
destination location associated with length of traversal time; (b)
select a route of travel based on the received real-time data
pertaining to the selected destination location, live traffic info
associated with a selected departure location, and live traffic
info associated with the selected destination location; (c)
determine a departure time for a predetermined arrival time at the
selected destination location, the determination based on the
selected route of travel, the selected departure location, and the
selected destination location; and (d) transmit, to the user
equipment, the determined departure time for the predetermined
arrival time and the selected route of travel associated with the
user equipment; and where the user equipment may be configured to:
receive, from the computing device via a push notification, the
determined departure time for the predetermined arrival time and
the selected route of travel associated with the user equipment,
thereby allowing the user of the user equipment to depart from the
selected departure location at a specified time in order to arrive
at the selected destination location at the predetermined arrival
time.
[0010] Optionally, the computing device may be further configured
to determine a departure time for a predetermined arrival time
based on prediction data associated with the selected destination
location, where the prediction data may comprise previously
collected real-time data and is received by the computing device on
a continual basis from the plurality of detection equipment.
Additionally, the real-time data and the previously collected
real-time data may be length of traversal time information related
to how fast a line is moving and at what rate the line was growing,
where the real-time data may be traversal information for the
selected destination location and where the prediction data may be
traversal information previously collected for the selected
destination location.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] Embodiments are illustrated by way of example and not
limitation in the figures of the accompanying drawing, and in
which:
[0012] FIG. 1 depicts a functional block diagram of a computing
system comprising a number of sensor devices in communication with
a networked computing device and a mobile device;
[0013] FIG. 2 depicts an exemplary embodiment of a computing system
that includes a user equipment (UE), a plurality of sensors
devices, and a networked computing device connected to a data
store;
[0014] FIG. 3 illustrates an exemplary top-level functional block
diagram of a computing device embodiment;
[0015] FIG. 4 depicts a functional block diagram of a networked
computing device embodiment in communication with a prediction data
component and real-time data component;
[0016] FIG. 5 depicts a graphical representation of the
notification of line fullness; and
[0017] FIG. 6 is a flow chart of an exemplary top-level functional
process of a server computing device embodiment.
DETAILED DESCRIPTION
[0018] The present application discloses methods, devices, and
systems for allowing a traveler or user to anticipate travel time
to, for example, an airport, and wait times at lines at the
exemplary airport. Additionally, different routes may be suggested
to the user to help them--once notified of the travel times--to
traverse such routes in a timely manner. An autonomous traversal
determination system is disclosed as comprising a number of
sensors, processors, and mobile devices.
[0019] Disclosed are systems and devices for, and methods of,
determining departure and total traversal durations for traveling
from a current location to a final destination; and more
particularly, to methods and devices for dynamically gathering
information related to the potential travel time and wait time at
transport facility lines. Embodiments of the autonomous traversal
determination system may detect or measure a bottleneck or delay
property and transmit such information to a server computing
device. Such information may optionally be collected from other
user devices travelling in similar areas and traversing similar
routes. The server computing device may then determine a total time
necessary for arriving at the destination transportation facility
and then transmitting that information to the user, e.g., traveler,
to help plan their departure. Thereby, the server computing device
may provide an autonomous system for the determination of departure
times and keeping a user informed of when they need to depart from
their current location in order to not only arrive at the
destination facility but also to traverse any hurdle, such as
lines, for arrival at a final destination within the destination
facility.
[0020] FIG. 1 is an exemplary functional block diagram depicting an
embodiment of an autonomous traversal determination system 100.
Embodiments of the autonomous traversal determination system 100
may be executed in real time or near real time. In this exemplary
functional block diagram, a plurality of detection equipment, e.g.,
sensor devices 110, 115, 120, may be connected to a communication
medium 150 via a router, where the communication medium 150 also
effects connecting a networked computing device 145, e.g., server,
and a mobile device 140. Via the communication medium 150 the
sensor devices 110, 115, 120 may continuously transmit data
pertaining to the flow of conveying of people or goods from place
to place, to the networked computing device 145 for processing. The
transmission may be asynchronous, meaning as not requiring a common
clock between the communicating devices; or a scheme for
synchronous notification may be utilized. The networked computing
device 145 may determine an estimation of time required for
traversing the obstacles based on the transmitted data from the
sensor devices 110, 115, 120, combined with other information
acquired relating to, for example, traffic. Subsequent to the
determination of the estimated time, the departure information may
then be determined based on the estimated traversal and
communicated to the mobile device 140, for example, as a push
notification.
[0021] Embodiments of the autonomous traversal determination system
100 may, via sensor devices 110, 115, 120 track persons or objects
on the move at the actual transport facility lines and provide a
timely ordered sequence of respective location data to a networked
computing device 145, e.g., capable of depicting the motion, and
determine the length of time required to transverse the line. The
sensor devices 110, 115, 120 may detect movement or changes in the
area they are designated to cover, and then provide a corresponding
output to be transmitted to a local computing device or via the
communication medium 150 to a networked computing device 145
outside of the local network. In one embodiment, each sensor device
may be equipped with its own communication system, for example, a
transceiver or just a transmitter, without the need to communicate
with the other sensor devices. Other embodiments may comprise a
system of sensors connected to each other via encoded messages as a
sequence of signals using a specific channel, where the information
collected may be grouped together and transmitted in real-time or
near real-time to computing devices for processing. Optionally,
information from mobile devise of other users may be used in lieu
of, or in addition to, sensor data.
[0022] Embodiments of the autonomous traversal determination system
utilize a departure determining tracking system used for providing
line-tracking services, for the exemplary purpose of putting users
and consumers on notice of the latest possible time they should
leave to their destination transport facility, e.g., airport. The
system may perform this by combining: [0023] (1) Map
data--indicates how long a specific route to the airport--given
traffic--should take based upon either the consumers current
location or a desired location; [0024] (2) Line Data--sensors in
the line posts that may track: (a) how full either the airline's
check-in line or (b) the airport's security line/TSA line is at a
given time (where the tracking is done based on an exemplary
scaling factor of 0-100%); and [0025] (3) Calculation and
Transmission of information--The information from the sensors in
each post may be transferred--either via Wi-Fi, Bluetooth
technology, or other technological means--to a secure location
where all of the information may be processed and combined to
determine a time to leave for the airport. The determined time may
then be transmitted to the consumer via email, SMS, MMS, telephone
call, or an application notification, e.g. push notification,
alerting them of the time needed to depart.
[0026] FIG. 2 depicts, in a functional block diagram, one
embodiment of the autonomous traversal determination system 200,
where the system may combine collected real-time and historical
traffic data with real-time and historical line wait time data.
This may be accomplished via, for example, accessing a remote data
store 260, i.e., database or collecting and accumulating such
information from a plurality of user mobile devices 240. That is,
the line tracking system may use an underlying map service (i.e.,
Google Maps, Waze, Apple Maps), at the start of the consumer
experience to provide the consumer real-time information relating
to how long it will take them to get from either: (a) their current
location or (b) a desired location. The map information may, for
example, provide an accurate estimation, as is currently done with
all map services, on how long the trip should take given traffic
changes and other instances that affect the time it takes to move
through traffic. The networked computing device 245 may then
combine that information related to traffic with information
received from sensor devices 210, 215. In this embodiment, the
sensor devices 210, 215 may via a series of transceivers 220, 225
communicate the information to a wide area network (WAN) 250
extending over a large geographical distance, with the networked
computing device 245 as the destination. Once received, the
networked computing device 245 may determine an appropriate
departure time for the mobile device 240 based on the historical
data received from the data store 260 and information received from
the sensor devices 210, 215.
[0027] FIG. 3 illustrates an exemplary top level functional block
diagram of a computing device embodiment 300. The exemplary
operating environment is shown as a computing device 320 comprising
a processor 324, such as a central processing unit (CPU),
addressable memory 327, an external device interface 326, e.g., an
optional universal serial bus port and related processing, and/or a
Communication or Network Communication port and related processing,
and an optional user interface 329, e.g., an array of status lights
and one or more toggle switches, and/or a display, and/or a
keyboard and/or a pointer-mouse system and/or a touch screen.
Optionally, the addressable memory may, for example, be: flash
memory, EPROM, and/or a disk drive or other hard drive. These
elements may be in communication with one another via a data bus
328, and via an operating system 325 such as one supporting a web
browser 323 and applications 322, the processor 324 may be
configured to execute steps of a process for determining the
departure and total traversal durations for traveling from a
current location to a final destination.
[0028] Additionally, embodiments may be implemented as an
application running on a mobile device, e.g., smartphone, or be
implemented as a web based service. Embodiments of the line
tracking system may be disclosed by example, as devices, systems,
and methods, and may be embodied as an application running on one
or more processors, e.g., an Apple.RTM., Google.RTM. Android,
and/or Windows.RTM. phone application running on a smartphone
and/or one or more remote servers and/or computers. That is, a
scheme for taking into account how long it may take to make it to
the actual airport based on traffic conditions, may be implemented
where the time to travel to the airport may be combined with how
long it may take to traverse the lines at the airport. Accordingly,
the total time necessary to make it from one's present location, or
anticipated location, to the gate of an airline may be precisely
predicted and determined.
[0029] Embodiments of the autonomous traversal determination system
provide techniques, where in addition to the traffic data, the
system may use a prediction method that takes into account the
actual wait time for specific lines at the transportations
facility, for example, airport. Accordingly, the system may
estimate total travel time from a specific location to an airline
gate at the airport with speed and accuracy. In this embodiment,
sensors may be utilized and embedded in the areas surrounding lines
associated with the traveler or user's itinerary to collect data
and report that data to the line tracking system. For example, a
sensor may detect events or changes in its environment, and then
provide a corresponding output; where a sensor may be a type of
transducer; and where sensors may provide various types of output,
but typically use electrical or optical signals. In one exemplary
embodiment, the sensors may be placed or embedded within the line
posts thereby having close proximity to the other people and
travelers standing in line. Other means or utility well known in
the art may also be used. Thereby, sensors--placed in areas where a
line may be formed at the particular facility that a specific
traveler or user may be required to wait in and pass--may measure
physical quantities and convert them into signals that can be read
by observers or by instruments. More particularly, such signals may
be received by a computing device that may be in communication with
a user equipment, e.g., handheld device, being used by the traveler
or user.
[0030] FIG. 4 depicts an embodiment, in a functional block diagram,
of the autonomous traversal determination system 400 where the
networked computing device 445 may be in communication through a
communication medium 450 with a prediction data component 470 and
real-time data component 480. The combination of historical data
for prediction purposes along with real-time data and traffic
predication technology may enable the system to accurately predict
a total length of time which may be required to not only arrive at
the destination but also to traverse any obstacles necessary in
order to timely accomplish arrival at a location within, for
example, a transportation facility or event stadium. By the
autonomous traversal determination system 400 using sensors within
a facility, the need for line of sight may no longer be required
for a location and traversal determination. This is a significant
advantage in certain applications since a GPS signal may be lost
indoors and current methods of arrival prediction may not suffice.
It is well known that within a transportation facility or public
event it may be extremely difficult to anticipate amount of time
needed to traverse certain sections or lines. For example, at a
public gathering or assembly, at sporting events, at conventions,
airports, train stations, etc., a person's ability to get around to
different areas and destinations within the venue may greatly be
affected depending on a number of factors.
[0031] In order to account for the aforementioned factors, the
autonomous traversal determination system 400 may, as depicted in
FIG. 4, request 444 prediction data and in return receive
prediction data information 445 from the prediction data component
470 on a continual basis. The autonomous traversal determination
system 400 may also request 448 real-time data and cause real-time
data information 448 to be transmitted from the real-time data
component 480. In one exemplary embodiment, the networked computing
device 445 may implement a time-based dependence of the system's
output on present and past inputs, i.e., hysteresis affect. That
is, the prediction data component 470 may process the past inputs
and transmit prediction data 445 to be used in conjunction with
received real-time data 447 from the real-time data component 480.
In addition, the prediction data component 470 and the real-time
data component 480 may be in direct communication 441, 442 with
each other where the prediction data component 470 may take as
input real-time data readings received from sensor devices at the
destination location. As described, some exemplary prediction data
associated with the traversal time at a specific location, may
include the time of day and historical information of how many
staff are working, how fast the particular staff works, or how
crowded the lines are during that time, how full a flight may be or
how many tickets have been purchased, how full the check-in line at
the traveler's desired airline is during that season, and data
relevant to traversing such line which may be affected based on a
number of different factors, such as: time, date, season, schedule,
and/or any other human trends.
[0032] Accordingly, the system, via sensors embedded in each of the
line posts, either in the form of lasers, sensors, cameras, etc.,
may determine the number of people in the line and how long it
should take for a traveler at the line's current "fullness" to make
it from the back to the front of the line. The system may take into
account, for example, the time of day and historical information of
how many staff are working, how fast the particular staff works or
how crowded the lines are during that time. Additionally, data
related to how full a flight may be or how many tickets have been
purchased, i.e., whether event is sold out, may be used. In an
exemplary embodiment, by calculating how full the check-in line at
the traveler's desired airline is, data relevant to traversing such
line may be made available to the traveler or user who has not yet
reached the airport. As the sensors are placed in the post, the
presence of an individual breaking a sensor's path, given the
posts' location in the chain of posts may indicate that the line
has gotten to that post's position and thus the line is that full.
Additionally, given the sensor readings, the system may determine
how fast the line is moving and at what rate the line may be
growing. In one embodiment, this information may be transmitted
continuously, via Wi-Fi or Bluetooth, to a server or prediction
data component so that patterns may be determined and identified,
thereby allowing better estimations to be made and presented to the
traveler or user.
[0033] The line tracking system may also include a Global
Positioning System (GPS) providing information on the user's
location so as to facilitate the real-time updating of information
related to the user's current status in relation to the airport
lines. That is, the system may prepopulate information on the
user's location and movement relating to the current itinerary
based on the location of the device. Accordingly, that information
may be viewable to the consumer on the web service/application as
provided in the exemplary illustration of FIG. 5. FIG. 5 depicts a
scenario where the notification conveys: "The Line You are
Currently Looking at is 70% full, given the day, date and time of
your estimated arrival to the airport, it should take you 35
minutes to go from start to finish of the line."
[0034] The exemplary embodiments of the networked computing devices
relate to techniques for determining an appropriate time for a
traveler or user to leave their current destination and make it to
their flight or event. These embodiments may apply to broadcast
networks, wired or wireless, and to specifications or standards,
including those that may later be developed. In one embodiment,
sensor readings may be streamed to mobile devices using wireless
local area network (WLAN) products that may be based on the
Institute of Electrical and Electronics Engineers' (IEEE) 802.11
standards, for example, wireless WiFi.RTM., or other wireless
networks with broadcast methods such as Long Term Evolution (LTE).
The mobile devices may act as a display and show, for example,
multiple views of potential lines the user has to traverse to get
to their final destination, e.g., airline gate. Devices that may
use WLAN, for example, mobile phones, specifically smartphones,
personal computers, tablets, and/or digital audio players, may
connect to a network resource such as the Internet via a wireless
network access point. In one embodiment, the system may manage
large numbers of mobile devices in a crowded environment; via, for
example, sending push notifications at a time that user needs to
leave their current location in order to make it to the destination
on time. Such notifications may be determined on a continuous
manner and periodically updated.
[0035] The system and method embodiments may provide a computing
device, having a processor and memory, for receiving the
information transmitted by the sensors for processing and
communicating to the mobile devices of the users. The method may
include receiving a set of sensor readings associated with each
line at a particular location and then storing the information in a
data store for the appropriate location. The information may then
be made available based on a set of requests. The system may then
associate a user with a specified path to their destination, where
the path may include the travel route to get to the transportation
facility and the route they need to take once inside, to get to
their desired gate for departure. A list of paths may then be
retrieved that is determined based on the shortest travel time,
wait time, and distance for the user. Once a selection of the path
is made by the user, the computing device, e.g., a processor and
resource for storing information, may determine a time interval
necessary to achieve the arrival at the final destination. A
synchronous, asynchronous, or combinations thereof, computing may
use the corresponding information to retrieve and alert the user of
the time they need to depart from their location or another
location. In some embodiments, a secondary process may be created
to monitor in real-time the travel time previously calculated and
update it according to any changes to the traffic and/or wait time.
Accordingly, the departure time of the user, i.e., total time, may
be updated in real-time allowing the user to update their
plans.
[0036] Exemplary embodiments of the line track system may track
multiple lines that may be necessary for the user to traverse. For
example, check-in line time and security line time at the remote
location, e.g., airport, may both be tracked via the exemplary
sensors and based on historical data in conjunction with past and
present trends, determine an estimation of how long a currently
composed line will take for the traveler or user to make his/her
way from start to finish. Accordingly, as many lines as necessary
may be monitored and considered in the prediction process.
[0037] The embodiment may comprise a recipient device comprising an
operating system and a data store, a sensor device comprising an
operating system and a data store, and a computing device
comprising an operating system and a data store. The system effects
the streaming of the line wait-time information data based on a
request received from a traveler or user of the operating device.
The devices may comprise an application program running on the
operating system to process streaming of line wait-time information
that may have been synchronized with other information. That is,
the sensor device may then communicate the line wait-time
information along with a set of associated information to the
recipient device which will then be able to display/relay the
relevant information.
[0038] The sensor device may transmit the associated information to
the recipient device via the server computing device and via, for
example, wireless WiFi.RTM., wireless local area network (WLAN), or
other wireless networks with broadcast methods such as Long Term
Evolution (LTE), Bluetooth, and/or any other hardware or software
radio broadcast methods. The server computing device may connect
and work with any such devices that may use LTE or WLAN, for
example, mobile phones, specifically smartphones, personal
computers, tablets, televisions, and/or digital cameras, to connect
to a network resource such as the Internet via wired or wireless
communication.
[0039] The computing device, or server, that is configured to
execute these steps may be a link processing component that links
the sensor data and the traffic data--that may have been acquired
by a data acquiring component--with each other. If the relevant
information data is not present, the link processing component may
query a separate component, for example, a data acquiring
component, to acquire the corresponding data and store it in a
storage component so as to determine the prediction time for
traversing to the desired destination. Some embodiments may support
the two steps as the traffic portion of the service and the line
tracking portion of the service that when added together may
provide an accurate estimation of the best time for a traveler to
head to the airport. The sensors in the posts and the accumulation
of data from those posts using sensors/lasers/cameras and the
transmission of that data via Bluetooth or Wi-Fi may be
incorporated for methods of performing the disclosed
determinations. As such, the method may also include downloading
and displaying data in real-time on the user device whereby the
user may then make their own determinations as well as following
the prediction data provided by the line tracking system.
[0040] In one embodiment, the data communication between the
devices may be via, for example, a User Datagram Protocol (UDP)
which is a transport layer protocol defined for use with the IP
network layer protocol. In one exemplary embodiment, a push data
mechanism may be implemented via TCP/IP protocols and the line
tracking time updates may be sent in real-time. Each mobile device
may comprise an embedded web application server that may allow
executable applications or scripts, e.g., application software,
that may be available in versions for different platforms and are
to be executed on the mobile device. Applications may be developed
to support various mobile devices and their respective operating
systems such as: iOS, Android, and Windows.
[0041] FIG. 6 is a flow chart of an exemplary top-level functional
process of a computing device embodiment that may include an
exemplary method of implementation of a computing device that
determines a departure time for a predetermined arrival time at the
selected destination location. The exemplary method of the system
and associated computing devices may comprise the following steps:
receiving, by a computing device comprising a processor and
addressable memory, from a plurality of detection equipment,
real-time data pertaining to a selected destination location,
wherein the real-time data comprises detected changes in
surrounding environments at the selected destination location
associated with length of traversal time (step 610); selecting, by
the computing device, a route of travel based on the received
real-time data pertaining to the selected destination location,
live traffic info associated with a selected departure location,
and live traffic info associated with the selected destination
location (step 620); determining, by the computing device, a
departure time for a predetermined arrival time at the selected
destination location, the determination based on the selected route
of travel, the selected departure location, and the selected
destination location (step 630); and transmitting, by the computing
device to the user equipment, the determined departure time for the
predetermined arrival time and the selected route of travel
associated with the user equipment, thereby allowing the user of
the user equipment to depart from the selected departure location
at a specified time in order to arrive at the selected destination
location at the predetermined arrival time (step 640).
[0042] The illustrations and examples provided herein are for
explanatory purposes and are not intended to limit the scope of the
appended claims. This disclosure is to be considered an
exemplification of the principles of the invention and is not
intended to limit the spirit and scope of the invention and/or
claims of the embodiment illustrated. It is contemplated that
various combinations and/or sub-combinations of the specific
features, systems, methods, and aspects of the above embodiments
may be made and still fall within the scope of the invention.
Accordingly, it should be understood that various features and
aspects of the disclosed embodiments may be combined with or
substituted for one another in order to form varying modes of the
disclosed invention. Further, it is intended that the scope of the
present invention herein disclosed by way of examples should not be
limited by the particular disclosed embodiments described
above.
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