Definition
Behavior analytics is a security approach that uses AI to analyze movement and activity patterns in camera footage to detect unusual behavior. In BehaviorWatch, this is implemented as a system that monitors multiple video feeds, detects anomalous patterns, and prioritizes threats in real time.
The difference from classic camera monitoring is this: the system doesn't just record footage, it evaluates whether the movement in that footage is "normal or not" and generates a prioritized alert accordingly.
How anomaly detection works
The system identifies unusual behavior patterns, suspicious movements, and deviations from normal activity using deep learning models trained on diverse scenarios.
Behavior pattern analysis
BehaviorWatch learns normal activity patterns for each zone and time period, automatically flagging deviations that may indicate security concerns.
The practical result of this approach is that the same movement can be evaluated differently depending on the zone or time of day -- because the system learns a separate definition of "normal" for each zone and time period.
Multi-feed monitoring
Another component of behavior analytics is the simultaneous analysis of dozens of camera feeds. BehaviorWatch processes these feeds together, correlating events across multiple locations to build a comprehensive situational picture.
The result is a combined picture built from data across multiple points, rather than an isolated signal from a single camera.
Behavior analytics in BehaviorWatch
BehaviorWatch is AI-powered behavior analysis that monitors multiple video feeds, detects anomalous patterns, and prioritizes threats in real time. The goal is to turn existing cameras into an intelligent security network.
This is achieved through anomaly detection, behavior pattern analysis, and multi-feed monitoring working together.
