SYSTEM AND METHOD FOR NEIGHBORHOOD-SCALE VEHICLE MONITORING

• US 20140334684A1
• Filed: 08/20/2013
• Published: 11/13/2014
• Est. Priority Date: 08/20/2012
• Status: Abandoned Application

• Current Assignee: Jonathan Strimling
• Original Assignee: Jonathan Strimling
• Inventors: Strimling, Jonathan
• Application Number:
  US14/361,304
• Publication Number:
  US 20140334684A1
• Time in Patent Office: Days
• US Class Current: 382/105
• CPC Class Codes: B60R 25/102 a signal being sent to a remote location, e.g. a radio signal being transmitted to a police station, a security company or the owner
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 20/63 Scene text, e.g. street names
• CPC Class Codes: G07C 9/28 the pass enabling tracking or indicating presence
• CPC Class Codes: G08G 1/123 indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, tramstransmission of navigation instructions to vehicles G08G1/0968

Abstract

A system and method may include a station to identify a vehicle and to determine a characterizing feature of the vehicle. An imager that is located remotely from the station is configured to acquire an image of the vehicle that includes the characterizing feature. A processor is configured to detect the characterizing feature in the acquired image and to associate the detected characterizing feature with the identified vehicle so as to predict a location of the vehicle.

Claims

1. A system comprising:

a station to identify a vehicle and to determine a characterizing feature of the vehicle;

an imager located remotely from the station, the imager to acquire an image of the vehicle that includes the characterizing feature; and

a processor to detect the characterizing feature in the acquired image and to associate the detected characterizing feature with the identified vehicle so as to predict a location of the vehicle.

2. The system of claim 1, wherein the station is configured to indicate a time at which the vehicle is identified and the imager is configured to indicate a time at which the image was captured.

3. The system of claim 2, wherein the processor is configured to predict a time of arrival of the vehicle at the imager.

4. The system of claim 1, wherein the station comprises a license plate reader to identify the vehicle by reading a license plate of the vehicle.

5. The system of claim 1, wherein the station comprises a radiofrequency identification device for to identify the vehicle by reading an radiofrequency identification tag of the vehicle.

6. A system for predicting an identity of a vehicle detected by multiple sensors, the system comprising:

a first sensor in a first location to detect a unique identifier of said vehicle;

a second sensor in a second location, said second sensor suitable to capture a second identifier of said vehicle, said second sensor not suitable to detect said unique identifier;

a processor, said processor to associate said unique identifier with said second identifier, and to predict that said vehicle detected by said second sensor in said second location is said vehicle detected by said first sensor in said first location.

7. The system of claim 6, wherein said first sensor comprises a license plate reader, and wherein said unique identifier comprises a license plate identifier, and wherein said first sensor is to detect at said first location said license plate identifier.

8. The system of claim 6, wherein said second sensor comprises an imager, said imager in said second location suitable to capture from said second location an image of said vehicle, said image comprising said second identifier of said vehicle.

9. The system of claim 6, wherein one or more instances of the first said sensor encompass the set of entry points of a vehicle to an area.

10. The system of claim 6, comprising a memory, said memory to store a time interval of said vehicle'"'"'s travel between said first location and said second location, and wherein said processor is to compare said time interval to a prior time interval associated with travel between said first location and said second location.

11. The system as in claim 10, wherein said processor is to compare a velocity of said travel between said first location and said second location with a prior velocity of said vehicle at a point between said first location and said second location.

12. A method for vehicle monitoring, the method comprising:

operating a sensor to automatically identify a vehicle at a first time at a first location;

determining a characterizing feature of the identified vehicle;

operating an imager to acquire an image at a second time at a second location; and

if the acquired image includes the characterizing feature, predicting a location of the vehicle.

13. The method of claim 12, wherein the sensor comprises a license plate reader and identifying the vehicle comprises reading a license plate of the vehicle.

14. The method of claim 12, wherein the sensor comprises an radiofrequency identification reader and identifying the vehicle comprises reading an radiofrequency identification tag of the vehicle.

15. The method of claim 12, wherein determining the characterizing feature comprises acquiring an image of the vehicle concurrently with identifying the vehicle.

16. The method of claim 12, wherein determining the characterizing feature comprises retrieving the characterizing feature from a database.

17. The method of claim 12, wherein the first location comprises an access point to a neighborhood.

18. The method of claim 12, wherein the second location comprises a vicinity of a residence.

19. The method of claim 12, wherein predicting the location comprises determining an expected time of travel from the first location to the second location.

20. The method of claim 12, comprising issuing an alert when the vehicle is predicted to be at a location that is not expected for that vehicle.