According to a survey of law enforcement professionals conducted by my company, Genetec, over 65% of violent crimes occur at night, and clearance rates are approximately 15% lower for night time crimes versus daytime offenses. The survey also indicates that 60% of crimes involve a vehicle.
When a witness is providing information about a crime involving a vehicle, they often can’t recall a license plate number, but they can recall the type of vehicle, the color, and even some identifying details such as approximate speed or unique characteristics. With technology that’s limited to license plate recognition, those valuable details about the vehicle can’t be acted upon without sifting through hours of video or volumes of still images, delaying the investigation process.
The Solution
To aid law enforcement professionals in the investigation of crimes involving vehicles,
Genetec has developed AutoVu Cloudrunner
, a cloud-based vehicle-centric investigation system (VCIS). It utilizes the all-new Cloudrunner CR-H2, a high-performance, solar-powered ALPR camera that detects highly accurate vehicle identification data day or night, rain or shine.
Powered by the AutoVu Machine Learning Core, a deep neural network-based vehicle recognition analytics engine, the CR-H2 camera goes beyond license plate recognition to collect, analyze, and securely store vehicle information such as vehicle color, type, and make, as well as behavior analytics, including speed and direction of travel. This allows investigators to narrow their search even when they do not have or only have partial license plate information available. The Machine Learning Core can also produce results from a vague vehicle description.