Assessment of electronic sensor data to remotely identify a motor vehicle and monitor driver behavior

• US 9,104,538 B2
• Filed: 06/06/2013
• Issued: 08/11/2015
• Est. Priority Date: 06/08/2012
• Status: Active Grant

• Current Assignee: Karma Automotive LLC (Wanxiang Group Corporation)
• Original Assignee: Airbiquity Incorporated
• Inventors: Mann, Darren, Garrett, Darrin
• Primary Examiner(s): Trammell, James
• Assistant Examiner(s): Malhotra, Sanjeev
• Application Number:
  US13/911,454
• Publication Number:
  US 20130332024A1
• Time in Patent Office: 796 Days
• Field of Search: 701/29, 701/34, 701/36, 701/51, 701/103, 701/104, 701/113, 701/115, 702/183, 705/14, 335/284, 340/441, 340/447, 123/472, 382/104, 348/143, 455/404.1
• US Class Current: 1/1
• CPC Class Codes: F04C 2270/0421 Controlled or regulated
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• 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: G07C 2205/02 using a vehicle scan tool
• CPC Class Codes: G07C 5/006 Indicating maintenance
• 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 5/0841 Registering performance data recording measured values G01D; information storage G11B
• CPC Class Codes: G07C 5/085 using electronic data carriers
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/55 Push-based network services

Abstract

A computing device is connected to a motor vehicle'"'"'s diagnostic port or communication port to acquire vehicle sensor data, for example from various pressure, temperature, oxygen, fuel and other sensors typically installed on a motor vehicle for other reasons. Acquired sensor data is wirelessly transmitted to a remote server where the acquired sensor data can be compared to a database of stored sensor data to identify the motor vehicle. Additional functionality is described that leverages uploaded sensor data. Sensor data may be uploaded to the server in near-real time, and/or buffered locally and uploaded by periodic or episodic, push or pull communication protocols.

Claims

1. A method for remotely identifying a motor vehicle, comprising:

(a) electronically acquiring sensor data from a plurality of electronic sensors installed in the vehicle;

(b) transmitting the acquired sensor data via a wireless link, from the vehicle to a remote server;

(c) at the remote server, receiving the acquired sensor data and comparing the acquired sensor data to baseline data stored at the remote server;

(d) identifying the motor vehicle based on the said comparison; and

(e) characterizing a vehicle'"'"'s dynamic state change to determine a rate of change profile for at least one of the plurality of electronic sensors installed in a given vehicle, and adding the dynamic state change profile to the stored baseline data for identifying the corresponding vehicle.

2. The method according to claim 1 wherein the stored baseline data includes sensor data previously acquired from a plurality of sensors on board each one of a plurality of motor vehicles.

3. The method according to claim 2 wherein the stored baseline data includes, for a selected vehicle, data acquired from at least three sensors selected from the group consisting of the following sensors—

engine coolant temperature

engine air temperature

fuel rail pressure

engine oil temperature

absolute throttle position limit

engine RPM at idle

Lambda exhaust oxygen sensor voltage.

4. The method according to claim 3 wherein the stored baseline data corresponding to at least one of the selected sensors includes first data acquired under a first operating condition of the corresponding motor vehicle, and second data acquired under a second operating condition of the corresponding motor vehicle.

5. The method according to claim 4 wherein the first operating condition of the corresponding motor vehicle is a cold condition and the second operating condition of the corresponding motor vehicle is a steady-state operating condition.

6. The method according to claim 5 wherein the steady-state operating condition is defined as a predetermined period of time after startup of the vehicle.

7. The method according to claim 1 wherein the dynamic state change is determined from a cold start condition to a predefined hot operating temperature.

8. The method according to claim 3 wherein said identifying the motor vehicle includes disambiguating among plural vehicles reporting similar sensor values, based on acquiring corresponding location data of each of the vehicles.

9. The method according to claim 8 wherein said acquiring corresponding location data of each of the vehicles from a GPS receiver located in the respective vehicle.