LOCATION AND EVENT CAPTURE CIRCUITRY TO FACILITATE REMOTE VEHICLE LOCATION PREDICTIVE MODELING WHEN GLOBAL POSITIONING IS UNAVAILABLE

• US 20160225072A1
• Filed: 04/11/2016
• Published: 08/04/2016
• Est. Priority Date: 12/31/2013
• Status: Active Grant

• Current Assignee: Spireon Incorporated (Solera Holdings Incorporated)
• Original Assignee: Spireon Incorporated (Solera Holdings Incorporated)
• Inventors: Brady, James, Estes, David, Marks, Thomas, Warner, Andy, Tran, Ben, Callinan, Michael, Collingwood, Chris, Withers, David, Ardelean, Ilie, Wheeler, Brian
• Granted Patent: US 10,223,744 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60R 16/0231 Circuits relating to the driving or the functioning of the vehicle monitoring tyres B60C23/00; indicating overspeed B60K31/00; for dash boards B60K37/00, B60Q3/10; for indicating emergencies B60Q1/52; brake control systems B60T; registering or indicating the working of vehicles G07C5/00; measuring distance G01C, e.g. combinations of speed and distance G01C23/00; engine indicators G01L; measuring speed or acceleration G01P
• CPC Class Codes: G01S 5/0027 of actual mobile position, i.e. position determined on mobile
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0841 Registering performance data recording measured values G01D; information storage G11B

Abstract

Disclosed are a device and/or a method of location and event capture circuitry to facilitate remote vehicle location predictive modeling when global positioning is unavailable. In one embodiment, a predictive circuit of a vehicle includes event detection circuitry to initiate a timer circuit of the vehicle when a wheel of the vehicle is in a stationary state beyond threshold amount of time during an event; an event categorization circuitry to monitor a telemetry data of the vehicle to assign a category to the event; a data communication circuitry to communicate the event, the category, and/or a set of other events and categories to a predictive recommendation server on a periodic basis; and a repossession detection circuitry to determine that the vehicle is pending repossession based on the event, the category, the set of other events and categories, and/or a message communicated from the predictive recommendation server to the predictive circuit.

Claims

1. A predictive circuit of a vehicle comprising:

an event detection circuitry to initiate a timer circuit of the vehicle when a wheel of the vehicle is in a stationary state beyond a threshold amount of time during an event;

an event categorization circuitry to monitor a telemetry data of the vehicle to assign a category to the event;

a data communication circuitry to communicate the event, the category, and a set of other events and categories to a predictive recommendation server on a periodic basis; and

a repossession detection circuitry to determine that the vehicle is pending repossession based on at least one of the event, the category, the set of other events and categories, and a message communicated from the predictive recommendation server to the predictive circuit.

2. The predictive circuit of the vehicle of claim 1:

wherein the event is associated with at least one of a time of day, a day of a week, a calendar day, and an event type by at least one of the predictive circuit and the predictive recommendation server;

wherein the event type is at least one of a home location, a work location, a day location, an evening location, a weekend location, a night location, and a holiday location.

3. The predictive circuit of the vehicle of claim 1:

wherein a location of the vehicle is determined through a triangulation algorithm of at least one of the data communication circuitry of the predictive circuit, and a mobile device associated with a user of the vehicle;

wherein the user of the vehicle is identified as at least one of a primary user of the vehicle, and a secondary user of the vehicle;

wherein the triangulation algorithm is applied to the mobile device when the mobile device is paired with the vehicle through a short range communication algorithm; and

wherein the mobile device is detected using the predictive circuit to have a latitudinal and longitudinal location change with nearby cellular towers in a pattern consistent with a movement of the vehicle.

4. The predictive circuit of the vehicle of claim 1, wherein the short range communication algorithm is at least one of Bluetooth®

, BLE®

, Zigbee®

, and another personal area network (PAN).

5. The predictive circuit of the vehicle of claim 1, wherein the telemetry data is determined based on at least one of an engine motor status, an accelerator status, a time of pause, a brake status, a park status, an occupant sensor status, a door status, a window status, a hood status, a truck status, a tailgate status, an in-car entertainment system status, an air-conditioning status, an in-car electronic system status, a neutral status and an other car status.

6. The predictive circuit of the vehicle of claim 1, wherein at least one of the predictive circuit and the predictive recommendation server to generate a statistical probability matrix of a set of predictive potential locations of the vehicle as a function of time based on an analysis of historical data.

7. The predictive circuit of the vehicle of claim 6:

wherein at least one of the predictive circuit and the predictive recommendation server to generate at least one of a stop report and a drive report; and

wherein at least one of the predictive circuit and the predictive recommendation server to determine an accuracy of the statistical probability matrix.

8. The predictive circuit of the vehicle of claim 6:

wherein an artificial intelligence algorithm is applied when generating the statistical probability matrix;

wherein the periodic basis is 25 hours to enable an hourly cycling of the event and the set of other events from the data communication circuitry to the predictive recommendation server; and

wherein the event data and the set of other events are transmitted in at least one of real time, an active period, and a batch mode from a locally stored cache storing event data since a previous transmittal to the predictive recommendation server.

9. A method of predictive circuit of a vehicle comprising:

initiating a timer circuit of the vehicle when a wheel of the vehicle is in a stationary state beyond a threshold amount of time during an event using a processor and a memory of an event detection circuitry;

monitoring a telemetry data of the vehicle to assign a category to the event using an event categorization circuitry;

communicating the event, the category, and a set of other events and categories to a predictive recommendation server on a periodic basis using a data communication circuitry; and

determining using a repossession detection circuitry that the vehicle is pending repossession based on at least one of the event, the category, the set of other events and categories, and a message communicated from the predictive recommendation server to the predictive circuit.

10. The method of predictive circuit of the vehicle of claim 9:

stopping the timer circuit when the wheel of the vehicle changes to a rotating state when the vehicle is in motion;

calculating a total time to stop using the time circuit; and

associating the total time to stop with the event.

11. The method of predictive circuit of the vehicle of claim 9:

associating the event with at least one of a time of day, a day of a week, a calendar day, and an event type by at least one of the predictive circuit and the predictive recommendation server;

wherein the event type is at least one of a home location, a work location, a day location, an evening location, a weekend location, a night location, and a holiday location.

12. The method of predictive circuit of the vehicle of claim 9:

determining a location of the vehicle through a triangulation algorithm of at least one of the data communication circuitry of the predictive circuit, and a mobile device associated with a user of the vehicle;

identifying the user of the vehicle as at least one of a primary user of the vehicle, and a secondary user of the vehicle;

applying the triangulation algorithm to the mobile device when the mobile device is paired with the vehicle through a short range communication algorithm; and

detecting the mobile device using the predictive circuit to have a latitudinal and longitudinal location change with nearby cellular towers in a pattern consistent with a movement of the vehicle.

13. The method of predictive circuit of the vehicle of claim 9, wherein the short range communication algorithm is at least one of Bluetooth®

, BLE®

, Zigbee®

, and another personal area network (PAN).

14. The method of predictive circuit of the vehicle of claim 9, further comprising determining the telemetry data based on at least one of an engine motor status, an accelerator status, a time of pause, a brake status, a park status, an occupant sensor status, a door status, a window status, a hood status, a truck status, a tailgate status, an in-car entertainment system status, an air-conditioning status, an in-car electronic system status, a neutral status and an other car status.

15. The method of predictive circuit of the vehicle of claim 9, generating a statistical probability matrix of a set of predictive potential locations of the vehicle as a function of time based on an analysis of historical data using at least one of the predictive circuit and the predictive recommendation server.

16. The method of predictive circuit of the vehicle of claim 15 further comprising:

generating at least one of a stop report and a drive report using at least one of the predictive circuit and the predictive recommendation serve; and

determining an accuracy of the statistical probability matrix using at least one of the predictive circuit and the predictive recommendation server.

17. The method of predictive circuit of the vehicle of claim 15:

applying an artificial intelligence algorithm when generating the statistical probability matrix;

enabling an hourly cycling of the event and the set of other events from the data communication circuitry to the predictive recommendation server through the periodic basis of 25 hours; and

transmitting the event data and the set of other events in at least one of real time, an active period, and a batch mode from a locally stored cache storing event data since a previous transmittal to the predictive recommendation server.

18. A predictive circuit of a vehicle comprising:

an event detection circuitry to initiate a timer circuit of the vehicle when a wheel of the vehicle is in a stationary state beyond a threshold amount of time during an event;

an event categorization circuitry to monitor a telemetry data of the vehicle to assign a category to the event;

a data communication circuitry to communicate the event, the category, and a set of other events and categories to a predictive recommendation server on a periodic basis;

a repossession detection circuitry to determine that the vehicle is pending repossession based on at least one of the event, the category, the set of other events and categories, and a message communicated from the predictive recommendation server to the predictive circuit;

wherein the predictive circuit to stop the timer circuit when the wheel of the vehicle changes to a rotating state when the vehicle is in motion;

wherein the timer circuit to calculate a total time to stop; and

wherein the total time to stop is associated with the event.

19. The predictive circuit of the vehicle of claim 18:

wherein the event is associated with at least one of a time of day, a day of a week, a calendar day, and an event type by at least one of the predictive circuit and the predictive recommendation server;

wherein the event type is at least one of a home location, a work location, a day location, an evening location, a weekend location, a night location, and a holiday location.

20. The predictive circuit of the vehicle of claim 18:

wherein a location of the vehicle is determined through a triangulation algorithm of at least one of the data communication circuitry of the predictive circuit, and a mobile device associated with a user of the vehicle;

wherein the user of the vehicle is identified as at least one of a primary user of the vehicle, and a secondary user of the vehicle;

wherein the triangulation algorithm is applied to the mobile device when the mobile device is paired with the vehicle through a short range communication algorithm; and

wherein the mobile device is detected using the predictive circuit to have a latitudinal and longitudinal location change with nearby cellular towers in a pattern consistent with a movement of the vehicle.