Citilog, the inventor of and a market leader in automatic real-time incident detection, says it is 100 per cent focused on minimising these high-impact problems.
Rather than rely on manually monitoring video feeds or reports from drivers, Citilog’s automated incident detection (AID) system identifies a range of events and incidents by leveraging deep learning to enhance the accuracy of video analytics.
The system is ‘trained’ with a large dataset of real-world traffic video clips to identify vehicles and set them apart from shadows and reflections. This reduces false positives and delivers unparalleled accuracy. These highly accurate detections enable traffic operators to act immediately, thus improving response times and relieving traffic build ups.
“Our proven software and unique accuracy turn cameras into automatic, state-of-the-art incident sensors,” says Eric Toffin CEO, Citilog. “For 25 years we have helped more than 2,000 customers in over 50 countries to create intelligent camera networks to dispatch emergency services and minimise the impact on city and highway traffic.”
The analytics software provides incident detection with alarms and associated video evidence within seconds of an occurrence.
One of many customers, the New York State Bridge Authority has been using Citilog since 2016 to enable its small team of operators to increase their situational awareness. Instead of discovering traffic incidents several minutes after they occur, the Citilog AID system sends an alert within seconds. They can then dispatch emergency services (in the case of an accident), crews to assist with disabled vehicles or debris clean-up, or inform drivers via VMS of slowdowns or alternate routes.
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