“Astra transforms existing video security systems from reactive and forensic solutions to proactive sources of preventive real-time intelligence,” said Ken LaMarca, CEO, Active Intelligence. “Unlike rules-based video analytics that look for specific events and behaviors, Astra detects events and activities of interest more often and more accurately than a live guard would, but at a fraction of the cost and without any distractions or fatigue.”

Active Intelligence’s innovative Astra Anomalous Detection Solution is engineered to detect an all-inclusive range of anomalies like a person lying on the ground, physical violence, fire and smoke, pedestrians walking in front of moving vehicles, thefts, vandalism, traffic jams, and much more. This extreme versatility also makes Astra ideally suited for a wide range of commercial and industrial business intelligence applications such as process manufacturing, logistics, and trafficking, to name a few. To reduce false alarms, Astra automatically ignores events like wind, small animals, shadows, and other normal events that may be common to a scene but may only occur occasionally.

Designed to work with the security industry’s leading VMS platforms, Astra already seamlessly integrates with Milestone Xprotect and Qognify’s Ocularis, with the Genetec Security Center currently under development. Additional VMS integrations are planned for 2023. These integrations will allow system operators to quickly, easily, and cost-effectively add the preventive anomalous detection features of Astra to their current systems without having to learn a new application.

A lightweight software application, Astra allows for hundreds of video streams to run on a single server, significantly reducing cost of implementation versus conventional video analytics software. Additionally, it imparts little to no load on the network. Astra is also private, secure, and unbiased, as it does not use human judgment or store personal identifiable data. All anomalous events and activities are identified based solely on statistical data.