There’s been a fundamental shift in artificial intelligence (AI)-driven analytics for video security systems. Traditionally used forensically to view recordings after an
incident occurred, most video systems are underutilized and the majority of video is never viewed. The development and deployment of deep-learning, object-based analytics based on neural networks have changed the value proposition for video surveillance. The move from motion-based to object-based analytics has fostered broader application and implementation of surveillance beyond security, encompassing operations, safety, logistics and business intelligence. Now, analytics can adeptly process high-traffic and complex scenes, classifying objects quickly and efficiently. It’s becoming a predictive tool, alerting proactively to changed scenes with the ability to recognize patterns with improved granularity, diversity and accuracy.
We’ve asked Matthew Cirnigliaro, video analytics marketing manager at Bosch, to address how analytics can benefit both the systems integrator and the end user with increasingly accurate data and information.
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