Automated Workplace Safety Monitoring Using AI Surveillance
An AI-powered computer vision system that monitors workplace video feeds in real time to detect safety violations, like missing PPE, unsafe zone entry, or unsafe behavior, and alerts supervisors instantly.
- AI / Automation
- Platform
- Python, SQL, Object Detection Models
- Stack
Brief
Manual safety monitoring on industrial sites and factory floors is inconsistent and reactive, violations (missing helmets/vests, restricted-zone breaches, unsafe machine operation) often go unnoticed until an incident occurs, exposing companies to compliance risk and workplace injuries.
Approach
Built a computer-vision-based monitoring system that processes live/recorded CCTV feeds using object detection and pose-estimation models to identify PPE compliance, restricted-zone breaches, and unsafe postures/behaviors in real time, triggering instant alerts to safety officers with logged incident evidence for audits.
Outcome
Enabled continuous, automated safety oversight instead of manual spot-checks, helping reduce compliance violations and supporting audit-readiness with a time-stamped incident log.
Built with
- Python
- SQL
- Object Detection Models
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