Systems and methods for telematics monitoring and communications

• US 9,164,957 B2
• Filed: 03/12/2013
• Issued: 10/20/2015
• Est. Priority Date: 01/24/2011
• Status: Active Grant

• Current Assignee: LexisNexis Risk Solutions, Inc. (RELX PLC)
• Original Assignee: LexisNexis Risk Solutions, Inc. (RELX PLC)
• Inventors: Hassib, Ash, Kaminski, Charles, Pierce, Aaron G
• Primary Examiner(s): Akintola, Olabode
• Application Number:
  US13/796,717
• Publication Number:
  US 20130190967A1
• Time in Patent Office: 952 Days
• Field of Search: 705/31.5, 340/439, 340/540, 340/933, 340/936, 701/1, 701/36
• US Class Current: 1/1
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• 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 5/0816 Indicating performance data, e.g. occurrence of a malfunction
• CPC Class Codes: G07C 5/085 using electronic data carriers
• CPC Class Codes: G07C 5/0858 wherein the data carrier is removable

Abstract

Certain example embodiments of the disclosed technology may include systems and methods for telematics monitoring. An example method is provided that includes receiving, at a mobile computing device, and from a Vehicle Identification Unit (VIU), identification (ID) data representing a first vehicle. The method further includes receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device. Certain embodiments may further include receiving, at an Operational Measurement Unit (OMU), an operation indication associated with the first vehicle. The OMU may include an operational measurement component configured to advance an operational count in response to receiving the operation indication. Certain example embodiments may include transmitting telematics data by the mobile computing device. In certain embodiments, the telematics data may include least a portion of one or more of the ID data, the sensor data, and/or the operational count data.

Claims

1. A computer-implemented method comprising:

receiving, at a processor, an operation indication associated with operation of a vehicle, wherein the operation indication comprises power being supplied to an on-board diagnostics (OBD) port associated with the vehicle;

responsive to receiving the operation indication, advancing an operational count of a vehicle power activated counter;

storing the operational count;

comparing the stored operational count with a previously stored count, wherein the previously stored count corresponds to a previously stored end-of-vehicle-operation operational count, and wherein the stored operational count corresponds to a start-of-vehicle-operation operational count, wherein the processor is further configured to provide an alert in response to the stored operational count and the previously stored count differing by greater than a predefined threshold; and

generating, responsive to the comparing, a monitor indication representing whether the vehicle has been monitored during a previous operation.

2. The method of claim 1, further comprising receiving vehicular identification data related to the vehicle, wherein the vehicular identification data comprises identification (ID) data representing the vehicle.

3. The method of claim 1, further comprising:

receiving and storing, at a server, telematics data associated with the vehicle;

comparing at least a portion of the received telematics data with telematics data associated with a plurality of other vehicles to determine one or more risk factors associated with operating the vehicle.

4. The method of claim 1, further comprising receiving and storing telematics data associated with the vehicle;

and outputting at least a portion of the telematics data in graphical format.

5. The method of claim 4, further comprising transforming the telematics data, wherein the transforming comprises one or more of formatting, filtering, compressing, or validating the received telematics data.

6. The method of claim 1, further comprising:

determining one or more entity scenarios comprising one or more assertions;

comparing one or more attributes of telematics data with information from one or more data sources to determine a plurality of correlations;

calculating a confidence level associated with the one or more assertions based at least in part on the determined plurality of correlations; and

outputting a score representative of the confidence level that the telematics data comprises one or more attributes that correspond to the one or more assertions.

7. The method of claim 6, wherein the information from one or more data sources comprises previously stored information having a class type corresponding to the telematics data, wherein the class type comprises accelerometer data, magnetometer data, gyroscope data, clock data, global positioning system (GPS) data, Bluetooth system data comprising one or more of paring or disconnects, microphone signals, or Wi-Fi system data.

8. The method of claim 6, wherein determining the one or more entity scenarios comprising one or more assertions comprises identifying one or more of an individual in possession of or associated with the mobile computing device, characteristics of an individual in possession of or associated with the mobile computing device, and a vehicle in proximity to the mobile device and associated with identification (ID) data representing the vehicle.

9. The method of claim 6, wherein the comparing one or more attributes of the telematics data with information from one or more data sources comprises comparing one or more of repeat location visits, repeatable events, velocity, acceleration, location at a specific operational, body patterns, habits, data attributes indicative of education level, data attributes indicative of age, data attributes indicative of gender, data attributes indicative of behavior risks, or groups of events.

10. A computer-implemented method comprising:

receiving, at a mobile computing device, an operation indication associated with operation of a vehicle, wherein the operation indication is received responsive to power being supplied to an on-board diagnostics (OBD) port associated with the vehicle, and wherein the operation indication advances an operational count of a vehicle power activated counter each time the vehicle is operated;

responsive to receiving the operation indication;

storing, in a memory associated with the mobile computing device, the operational count;

comparing the stored operational count with a previously stored count, wherein the previously stored count corresponds to a previously stored end-of-vehicle-operation operational count, and wherein the stored operational count corresponds to a start-of-vehicle-operation operational count, wherein the processor is further configured to provide an alert in response to the stored operational count and the previously stored count differing by greater than a predefined threshold;

generating, by the mobile computing device, and responsive to the comparing, a monitor indication representing whether the vehicle has been monitored during a previous operation; and

transmitting telematics data, wherein the telematics data comprises at least a portion of one or more of the operational count and the monitor indication.

11. The method of claim 10, further comprising receiving vehicular identification data related to the vehicle, wherein the vehicular identification data comprises identification (ID) data representing the vehicle, and wherein the telematics data further comprises the ID data.

12. The method of claim 10, further comprising:

receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device; and

transmitting, by the mobile computing device, telematics data, wherein the telematics data comprises at least a portion of the sensor data.

13. The method of claim 10, further comprising:

determining, based at least in part on the telematics data, one or more entity scenarios comprising identifying one or more of an individual in possession of or associated with the mobile computing device, characteristics of an individual in possession of or associated with the mobile computing device, and a vehicle in proximity to the mobile computing device.

14. The method of claim 10, wherein the telematics data further comprises accelerometer data, magnetometer data, gyroscope data, clock data, global positioning system (GPS) data, Bluetooth system data comprising one or more of paring or disconnects, microphone signals, and Wi-Fi system data.

15. The method of claim 10, wherein the telematics data further comprises one or more of repeat location visits, repeatable events, velocity, acceleration, location at a specific operational, body patterns, habits, data attributes indicative of education level, data attributes indicative of age, data attributes indicative of gender, data attributes indicative of behavior risks, and groups of events.

16. A system comprising:

at least one memory for storing data and computer-executable instructions; and

at least one processor configured to access the at least one memory and further configured to execute the computer-executable instructions to;

receive an operation indication associated with operation of a vehicle, wherein the operation indication comprises power being supplied to an on-board diagnostics (OBD) port associated with the vehicle;

advance an operational count of a vehicle power activated counter responsive to the operation indication;

store, in the memory, the operational count;

compare the stored operational count with a previously stored count, wherein the previously stored count corresponds to a previously stored end-of-vehicle-operation operational count, and wherein the stored operational count corresponds to a start-of-vehicle-operation operational count, wherein the at least one processor is further configured to provide an alert in response to the stored operational count and the previously stored count differing by greater than a predefined threshold;

generate, responsive to the comparing, a monitor indication representing whether the vehicle has been monitored during a previous operation; and

transmit telematics data, wherein the telematics data comprises at least a portion of one or more of the operational count and the monitor indication.

17. The system of claim 16, further comprising one or more sensors in communication with the at least one processor, and wherein the at least one processor is further configured to receive sensor date from the one or more sensors;

and wherein the telematics data further comprises at least a portion of the sensor data.

18. The system of claim 17, wherein the sensor data comprises accelerometer data, magnetometer data, gyroscope data, clock data, global positioning system (GPS) data, Bluetooth system data comprising one or more of paring or disconnects, microphone signals, and Wi-Fi system data.

19. The system of claim 16, wherein the at least one processor is further configured to receive vehicle identification (ID) data, and wherein the telematics data further comprises at least a portion of the ID data.

20. The system of claim 16, wherein the telematics data further comprises one or more of repeat location visits, repeatable events, velocity, acceleration, location at a specific operational, body patterns, habits, data attributes indicative of education level, data attributes indicative of age, data attributes indicative of gender, data attributes indicative of behavior risks, or groups of events.

21. A non-transitory computer-readable media that stores instructions that, when executed, cause one or more processors to perform a method comprising:

receiving, at a mobile computing device, an operation indication associated with operation of a vehicle, wherein the operation indication is received responsive to power being supplied to an on-board diagnostics (OBD) port associated with the vehicle, and wherein the operation indication advances an operational count of a vehicle power activated counter each time the vehicle is operated;

responsive to receiving the operation indication;

storing, in a memory associated with the mobile computing device, the operational count;

comparing the stored operational count with a previously stored count, wherein the previously stored count corresponds to a previously stored end-of-vehicle-operation operational count, and wherein the stored operational count corresponds to a start-of-vehicle-operation operational count, wherein the processor is further configured to provide an alert in response to the stored operational count and the previously stored count differing by greater than a predefined threshold;

generating, by the mobile computing device, and responsive to the comparing, a monitor indication representing whether the vehicle has been monitored during a previous operation; and

transmitting telematics data, wherein the telematics data comprises at least a portion of one or more of the operational count and the monitor indication.

22. The non-transitory computer-readable media of claim 21 that further stores instructions that, when executed, cause one or more processors to:

receive vehicular identification data related to the vehicle, wherein the vehicular identification data comprises identification (ID) data representing the vehicle, and wherein the telematics data further comprises the ID data.

23. The non-transitory computer-readable media of claim 21 that further stores instructions that, when executed, cause one or more processors to:

receive, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device; and

transmit, by the mobile computing device, telematics data, wherein the telematics data comprises at least a portion of the sensor data.

24. The non-transitory computer-readable media of claim 21, wherein the telematics data further comprises accelerometer data, magnetometer data, gyroscope data, clock data, global positioning system (GPS) data, Bluetooth system data comprising one or more of paring or disconnects, microphone signals, and Wi-Fi system data.