Electronic Surveillance Network System
First Claim
1. Electronic surveillance network system architectureSystem architecture that includes combined visual and SWIR detection system, embedded proximity detection system, controller, backend computing and decision support system, surveillance network information management server, integration broker, surveillance network front-end applications.
0 Assignments
0 Petitions
Accused Products
Abstract
We have defined an automated detection system consisting of a combined visible and Short Wave Infra-Red (SWIR) camera that identifies vehicle identification number and the number of occupants in a given vehicle, as well as the speed of the automobile. This information is processed in conjunction with law enforcement rules to determine whether the particular vehicle driver is in violation to enable the law enforcement personnel to issue traffic violation ticket and mail it to the registered driver'"'"'s address. Such an automated system could be placed at strategic locations along the stretch of the High Occupancy Vehicle (HOV) or carpool lanes and interconnected with backend computing and decision support system to assist law enforcement personnel in identifying vehicle driver violating the HOV or carpool lane rules and in issuing violation tickets to the registered driver of the particular vehicle.
-
Citations
9 Claims
-
1. Electronic surveillance network system architecture
System architecture that includes combined visual and SWIR detection system, embedded proximity detection system, controller, backend computing and decision support system, surveillance network information management server, integration broker, surveillance network front-end applications.
-
6. An algorithm and implementation to compute the speed of the approaching vehicle from captured images of multiple successive frames.
-
9. An ability to keep track of repeat offenders by creating and keeping a watch list of prior offenders (vehicles) as can be discerned from the license plates of the cars detected and not from facial recognition of the drivers since this algorithm only counts the number of occupants and does not identify the drivers for privacy reasons (based on recent history).
Specification