AI CCTV Video Monitoring Guide: Comparing Approaches and Deployment Steps

AI CCTV video monitoring uses artificial intelligence to analyze feeds from existing cameras, identify hazardous or unusual events in real time, alert designated personnel, and preserve video and response records, reducing the need for continuous manual observation of multiple screens. The approach is presented as relevant to both small workplaces that lack dedicated monitoring staff and large industrial sites where hundreds of cameras can overwhelm operators, with Korea’s provisional 2025 occupational fatality statistics illustrating that serious risks affect organizations of different sizes. Systems may use general foundation models without task-specific training, site-specific calibration to reduce false alarms, or specialized datasets and models for narrow tasks such as EV fire detection. Potential applications include construction safety, PPE compliance, forklift movement, industrial plants, logistics fleets, parking facilities, fire detection, and smart-city operations, with cited examples reporting improvements in compliance, reduced review time, and faster detection. Deployment generally depends on reusing compatible CCTV infrastructure, defining priority event types, establishing alert-response workflows, and accounting for hardware, software, customization, operations, camera volume, number of monitored events, and sites; however, the technology itself does not replace legal safety obligations or the need for documented human response procedures.

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