Systems and methods for telematics monitoring and communications

• US 10,438,424 B2
• Filed: 08/28/2015
• Issued: 10/08/2019
• 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:
  US14/838,508
• Publication Number:
  US 20150379789A1
• Time in Patent Office: 1,502 Days
• Field of Search: None
• 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 an operational measurement component associated with a mobile computing device, an operation indication of a vehicle, wherein the operational measurement component is configured to advance an operational count in response to receiving the operation indication, and wherein the operation indication is received responsive to a changed state of ignition of the vehicle;

comparing a first operational count with a second operational count, wherein the first operational count corresponds to a previously stored end-of-vehicle-operation operational count, and wherein the second operational count corresponds to a subsequently advanced start-of-vehicle-operation operational count responsive to the received operation indication at the operational measurement component;

generating an alert in response to the first operational count and second operational count differing by greater than a predefined threshold;

receiving, at a processor, telematics data comprising sensor data detected by sensors associated with the mobile computing device including location, acceleration, and angular position of the mobile computing device;

determining, by a processing engine, and based at least in part on the telematics data, one or more entity scenarios comprising a plurality of assertions, and wherein determining the one or more entity scenarios includes identifying characteristics of an individual in possession of or associated with the mobile computing device;

comparing, by the processing engine, one or more attributes of the telematics data with stored information from one or more data sources to determine a plurality of correlations to the plurality of assertions, wherein the one or more attributes of the telematics data include repeat location visits;

calculating, by the processing engine, a confidence level associated with the plurality of assertions based at least in part on the determined plurality of correlations; and

outputting one or more of;

an identity indication of an individual associated with the mobile computing device based at least in part on the confidence level, and the generated alert.

2. The method of claim 1, further comprising:

transmitting to a remote server, responsive to receiving the operation indication, a unique participant ID corresponding to the mobile communication device.

3. The method of claim 1, further comprising transmitting the generated alert to a remote server.

4. The method of claim 1, wherein the telematics data comprises one or more of:

repeat location visits, repeatable events, velocity, acceleration, location at a specific time, 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.

5. The method of claim 1, further comprising receiving, at the mobile computing device, vehicular identification data, wherein the vehicular identification data comprises identification (ID) data representing the vehicle.

6. A mobile computing device, comprising:

a processor; and

memory in communication with the processor and configured for storing computer-executable instructions that cause the processor to;

receive an operation indication associated with a vehicle;

advance an operational count in response to receiving the operation indication, wherein the operation indication is received responsive to an ignition of an associated vehicle being switched to an on state;

compare a first operational count with a second operational count, wherein the first operational count corresponds to a previously stored end-of-vehicle-operation operational count, and wherein the second operational count corresponds to a subsequently advanced start-of-vehicle-operation operational count responsive to the received operation indication;

generate an alert in response to the first operational count and second operational count differing by greater than a predefined threshold;

receive, from the one or more sensors, telematics data including location, acceleration, and angular position of the mobile computing device;

determine, based at least in part on the telematics data, one or more entity scenarios comprising a plurality of assertions, wherein determining the one or more entity scenarios includes identifying characteristics of an individual in possession of or associated with the mobile computing device;

compare one or more attributes of the telematics data with stored information from one or more data sources to determine a plurality of correlations to the plurality of assertions, wherein the one or more attributes of the telematics data include repeat location visits;

calculate a confidence level associated with the plurality of assertions based at least in part on the determined plurality of correlations; and

output one or more of;

an identity indication of an individual associated with the mobile computing device based at least in part on the confidence level, and the generated alert.

7. The mobile computing device of claim 6, wherein the mobile computing device is configured to receive vehicular identification, wherein the vehicular identification data comprises identification (ID) data representing the vehicle.

8. The mobile computing device of claim 6, further comprising one or more sensors in communication with the processor, wherein the mobile computing device is configured to receive, from the one or more sensors, sensor data based at least in part on an operation indication received in response to power being supplied to an ignition of a vehicle.

9. The mobile computing device of claim 6, further comprising one or more sensors configured to gather telematics data, wherein the telematics data comprises one or more of:

repeat location visits, repeatable events, velocity, acceleration, location at a specific time, 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.