System and method for smart, rational and collaborative location tracking for trip planners

• US 9,679,475 B1
• Filed: 04/05/2016
• Issued: 06/13/2017
• Est. Priority Date: 04/05/2016
• Status: Active Grant

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Inventors: Annamaneni, Narendra, Subramaniam T, Raja, Unny Edakunni, Narayanan, Feroz Aashik Salim, Mohammed
• Primary Examiner(s): Marc, McDieunel
• Assistant Examiner(s): Stroud, James E
• Application Number:
  US15/090,892
• Time in Patent Office: 434 Days
• Field of Search: 701117
• CPC Class Codes: G06F 2221/2111 Location-sensitive, e.g. geographical location, GPS
• CPC Class Codes: G08G 1/005 including pedestrian guidance indicator
• CPC Class Codes: G08G 1/123 indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, tramstransmission of navigation instructions to vehicles G08G1/0968
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/046 involving vehicles, e.g. floating traffic data [FTD] or vehicle traffic prediction
• CPC Class Codes: H04W 4/42 for mass transport vehicles, e.g. buses, trains or aircraft
• CPC Class Codes: H04W 84/22 with access to wired networks
• CPC Class Codes: Y02D 30/70 in wireless communication networks

Abstract

Methods and systems for collaborative location tracking. Commuters can be organized into a group according to commuter client devices (e.g., smartphones, tablet computing devices, etc.) respectively associated with the commuters. The commuter client devices are tracked as a group rather than individually and based on power efficient context-aware location data derived from the commuter client devices and a generated trip plan in association with data indicative of real-time dynamics so that power usage of individual commuter client devices is rationally minimized.

Claims

1. A method for collaborative location tracking, comprising:

grouping a plurality of commuters into a group with at least one server according to a plurality of commuter client devices respectively associated with said plurality of commuters; and

tracking with said at least one server said plurality of commuter client devices as said group rather than individually and based on power efficient context-aware location data derived from said plurality of commuter client devices and a generated trip plan in association with data indicative of real-time dynamics so that a power usage of individual commuter client devices among said plurality of commuter client devices is rationally minimized, wherein said generated trip plan is generated by said at least one server.

2. The method of claim 1 further comprising:

identifying at least one node within said group; and

providing a location of said at least one node to at least one other node within said group.

3. The method of claim 1 further comprising:

deriving GPS location data from a GPS system associated with a public transportation vehicle; and

sharing said location data among said plurality of commuter client devices.

4. The method of claim 1 further comprising creating a list of strategic tracking checkpoints for said group based on said power efficient context-aware location data, wherein said group tracks and logs locations of said groups at said checkpoints in said list of strategic tracking checkpoints rather than continuously.

5. The method of claim 1 wherein said tracking with said at least one server said plurality of commuter client devices as said group, further comprises:

tracking said plurality of commuter client devices utilizing said at least one server, which generates optimal grouping data and tracking data for said plurality of commuters.

6. The method of claim 2 wherein said at least one node comprises a mobile component of a mobile computing device, wherein said at least one node creates an ad-hoc group among said plurality of commuters and implements an optimal tracking plan provided by said server, said optimal tracking plan including said generated trip plan.

7. The method of claim 6 wherein said tracking with said at least one server said plurality of commuter client devices as said group, further comprises:

tracking said plurality of commuter client devices utilizing said at least one server, which generates optimal grouping data and tracking data for said plurality of commuters.

8. A system for collaborative location tracking, comprising:

at least one processor; and

a non-transitory computer-usable medium embodying computer program code, said computer-usable medium capable of communicating with said at least one processor, said computer program code comprising instructions executable by said at least one processor and configured for;

grouping a plurality of commuters into a group with at least one server according to a plurality of commuter client devices respectively associated with said plurality of commuters; and

tracking said plurality of commuter client devices with said at least one server as said group rather than individually and based on power efficient context-aware location data derived from said plurality of commuter client devices and a generated trip plan in association with data indicative of real-time dynamics so that a power usage of individual commuter client devices among said plurality of commuter client devices is rationally minimized wherein said generated trio plan is generated by said at least one server.

9. The system of claim 8 wherein said instructions are further configured for:

identifying at least one node within said group; and

providing a location of said at least one node to at least one other node within said group.

10. The system of claim 8 wherein said instructions are further configured for:

deriving GPS location data from a GPS system associated with a public transportation vehicle; and

sharing said location data among said plurality of commuter client devices.

11. The system of claim 8 wherein said instructions are further configured for creating a list of strategic tracking checkpoints for said group based on said power efficient context-aware location data, wherein said group tracks and logs locations of said groups at said checkpoints in said list of strategic tracking checkpoints rather than continuously.

12. The system of claim 8 wherein said instructions for tracking with said at least one server said plurality of commuter client devices as said group are further configured to include instructions for:

tracking said plurality of commuter client devices utilizing said at least one server, which generates optimal grouping data and tracking data for said plurality of commuters.

13. The system of claim 9 wherein said at least one node comprises a mobile component of a mobile computing device, wherein said at least one node creates an ad-hoc group among said plurality of commuters, and implements an optimal tracking plan provided by said server, said optimal tracking plan including said generated trip plan.

14. The system of claim 9 wherein said instructions for tracking said plurality of commuter client devices as said group are further configured to include instructions for:

tracking said plurality of commuter client devices utilizing a server that generates optimal grouping data and tracking data for said plurality of commuters.

15. A non-transitory processor-readable medium storing computer code representing instructions to cause a process for collaborative location tracking, said computer code comprising code to:

group a plurality of commuters into a group with at least one server according to a plurality of commuter client devices respectively associated with said plurality of commuters; and

track said plurality of commuter client devices with said at least one server as said group rather than individually and based on power efficient context-aware location data derived from said plurality of commuter client devices and a generated trip plan in association with data indicative of real-time dynamics so that a power usage of individual commuter client devices among said plurality of commuter client devices is rationally minimized, wherein said generated trip plan is generated by said at least one server.

16. The processor-readable medium of claim 15 wherein said code further includes code to:

identify at least one node within said group; and

provide a location of said at least one node to at least one other node within said group.

17. The processor-readable medium of claim 15 wherein said code further includes code to:

derive GPS location data from a GPS system associated with a public transportation vehicle; and

share said location data among said plurality of commuter client devices.

18. The processor-readable medium of claim 15 wherein said code further includes code to create a list of strategic tracking checkpoints for said group based on said power efficient context-aware location data, wherein said group tracks and logs locations of said groups at said checkpoints in said list of strategic tracking checkpoints rather than continuously.

19. The processor-readable medium of claim 15 wherein said code to track with said at least one server said plurality of commuter client devices as said group, further includes code to:

track said plurality of commuter client devices utilizing said at least one server, which generates optimal grouping data and tracking data for said plurality of commuters.

20. The processor-readable medium of claim 19 wherein said at least one node comprises a mobile component of a mobile computing device, wherein said at least one node creates an ad-hoc group among said plurality of commuters and implements an optimal tracking plan provided by said server, said optimal tracking plan including said generated trip plan.