Traditional physical security relies heavily on human monitoring, leaving organizations vulnerable to fatigue, gaps in coverage, and delayed emergency responses. AI-powered Intelligent Video Analytics (IVA) transforms standard CCTV video loops into proactive threat monitoring grids, utilizing computer vision models (such as YOLO and DeepSORT) to analyze events in real-time.
These AI surveillance platforms automatically spot security hazards—such as perimeter intrusions, smoke/fire indicators, abandoned packages, or crowds forming in restricted zones—and immediately send automated alerts. This changes reaction times from minutes of forensic searching to milliseconds of automated warning.
Deploying intelligent surveillance also requires balancing security needs with compliance standards. This paper explores implementing edge-based processing to blur faces and license plates automatically, preserving privacy and maintaining absolute compliance with GDPR and regional data handling frameworks.
