Calipsa has announced a new monitoring platform designed to provide real-time analytics to alarm receiving centres (ARCs) and help reduce the number of false security alarms every year. The platform is built on ‘Deep Learning’ models by machine learning and artificial intelligence experts.
With figures showing it costs the UK economy hundreds of millions of pounds a year in lost productivity due to false alarms being triggered by staff on site when a system is still armed, environmental issues and even insects on the camera, Calipsa is claiming to reduce false alarm rates by up to 50%, according to customer trials.
“Security cameras by their nature are sensitive and are often falsely triggered by pretty much anything from spiders to trees blowing in the wind,” explains Anthony Fulgoni, Sales Director, Calipsa. “Apart from human operators deciding the validity of an alarm, the current state of the art is either anti-dither settings, which allow you to set the length of the motion to be detected, and masking, which allows you to ignore certain parts of the camera view. But both of these solutions are archaic, but are still deployed even in modern day alarm receiving centres. They lack the capabilities to take into account a wide range of factors, mostly environmental.”
Calipsa’s integrated alarm receiving solution applies software to intercept false alarms, confirming their legitimacy and passing only genuine alarms to operators at the monitoring station.
Customers benefit from analytics developed using algorithms that can quickly process and analyse video feeds to detect humans, vehicles or animals at the scene, then filter out false alarms and detect real alarms –all in real time. Staff members are thus able to concentrate on legitimate alarms, and reduce the risk of missed incidents.
Designed to work with any existing IP camera or video source, the technology can be deployed via the cloud with no upfront investment.