SYSTEM AND METHOD FOR CROWDSOURCING VEHICLE-RELATED ANALYTICS

• US 20140277902A1
• Filed: 03/07/2014
• Published: 09/18/2014
• Est. Priority Date: 03/14/2013
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Telogis Incorporated (Verizon Communications Inc.)
• Inventors: Koch, Jason Mathew
• Granted Patent: US 9,384,597 B2
• Time in Patent Office: Days
• US Class Current: 701/29.1
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/0825 using optical means

Abstract

Currently vehicles typically include an engine computer that outputs diagnostic trouble codes (DTC) that are indicative of some fault condition in a vehicle. DTCs can tell a specific problem with a particular part such as that a cylinder in an engine is misfiring, but do not provide any indication as to the cause of the problem and do not propose any solutions for solving the problem. This disclosure advantageously describes systems that can analyze DTCs and other telematics data using crowdsourcing principles to recommend vehicle maintenance and other solutions.

Claims

1. A method of programmatically diagnosing vehicle problems, the method comprising:

under control of a hardware processor;

identifying a diagnostic trouble code output by a vehicle;

accessing community prognostics data associated with the diagnostic trouble code, the community prognostics data being generated responsive to input associated with a plurality of vehicles;

identifying a predicted diagnosis associated with the diagnostic trouble code from the community prognostics data; and

outputting the predicted diagnosis for presentation to a user.

2. The method of claim 1, wherein said identifying the diagnostic trouble code comprises programmatically identifying the diagnostic trouble code from telematics data associated with the vehicle.

3. The method of claim 2, wherein said identifying the diagnostic trouble code is performed substantially in real time.

4. The method of claim 2, further comprising identifying one or more of the following sensor data associated with the vehicle from the telematics data:

speed, temperature, acceleration, G-force, rotation force as from a gyroscope, position, an odometer reading, a blown-out tire sensor reading, and a tire pressure reading.

5. The method of claim 4, wherein said identifying the predicted diagnosis is further responsive to said identifying one or more of the following sensor data.

6. The method of claim 1, further comprising obtaining the community prognostics data from a plurality of users.

7. The method of claim 6, wherein said obtaining comprises outputting a user interface configured to provide functionality for each of the users to associate the diagnostic trouble code with one or more selected predicted diagnoses, including the predicted diagnosis.

8. Non-transitory physical computer storage comprising instructions stored therein that, when executed by a hardware processor, are configured to perform operations for programmatically diagnosing vehicle problems, the operations comprising:

identifying a diagnostic trouble code output by a vehicle;

accessing community prognostics data associated with the diagnostic trouble code, the community prognostics data being generated responsive to input associated with a plurality of vehicles;

identifying a predicted diagnosis associated with the diagnostic trouble code from the community prognostics data; and

outputting the predicted diagnosis for presentation to a user.

9. The non-transitory physical computer storage of claim 8, wherein said identifying the diagnostic trouble code comprises programmatically identifying the diagnostic trouble code from telematics data associated with the vehicle.

10. The non-transitory physical computer storage of claim 9, wherein said identifying the diagnostic trouble code is performed substantially in real time.

11. The non-transitory physical computer storage of claim 10, wherein the operations further comprise identifying one or more of the following sensor data associated with the vehicle from the telematics data:

speed, temperature, acceleration, G-force, rotation force as from a gyroscope, position, an odometer reading, a blown-out tire sensor reading, and a tire pressure reading.

12. The non-transitory physical computer storage of claim 11, wherein said identifying the predicted diagnosis is further responsive to said identifying one or more of the following sensor data.

13. The non-transitory physical computer storage of claim 8, wherein the operations further comprise obtaining the community prognostics data from a plurality of users.

14. The non-transitory physical computer storage of claim 13, wherein said obtaining comprises outputting a user interface configured to provide functionality for each of the users to associate the diagnostic trouble code with one or more selected predicted diagnoses, including the predicted diagnosis.

15. A system for programmatically diagnosing vehicle problems, the system comprising:

a hardware processor configured to;

identify a diagnostic trouble code output by a vehicle;

access community prognostics data associated with the diagnostic trouble code, the community prognostics data being generated responsive to input associated with a plurality of vehicles;

identify a predicted diagnosis associated with the diagnostic trouble code from the community prognostics data; and

output the predicted diagnosis for presentation to a user.

16. The system of claim 15, wherein the processor is further configured to identify the diagnostic trouble code by at least programmatically identifying the diagnostic trouble code from telematics data associated with the vehicle.

17. The system of claim 16, wherein the processor is further configured to identify the diagnostic trouble code substantially in real time.

18. The system of claim 16, wherein the processor is further configured to identify one or more of the following sensor data associated with the vehicle from the telematics data:

speed, temperature, acceleration, G-force, rotation force as from a gyroscope, position, an odometer reading, a blown-out tire sensor reading, and a tire pressure reading.

19. The system of claim 18, wherein the processor is further configured to identify the predicted diagnosis responsive to identifying the sensor data.

20. The system of claim 15, wherein the processor is further configured to obtain the community prognostics data from a plurality of users by at least outputting a user interface configured to provide functionality for each of the users to associate the diagnostic trouble code with one or more selected predicted diagnoses, including the predicted diagnosis.