This whitepaper compares traditional video analytics (TVA) with modern computer vision intelligence (CVI). TVA relies on rule-based detection, such as motion or tripwires, which often results in high false alarms and limited contextual understanding. As detailed in the problem statement, these systems struggle with scalability and cannot interpret behavior. CVI, powered by AI and machine learning, introduces context-aware analysis that evaluates actions, interactions, and environmental patterns in real time. It integrates with existing systems while reducing false positives and improving accuracy. The paper provides guidance on when to use each approach and highlights CVI as the foundation for scalable, intelligent, and proactive security operations.

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