Unauthorized Exit Monitoring

In high-risk and controlled environments, ensuring that workers remain within authorized zones is critical. However, manual monitoring at exit points is often inconsistent, difficult to scale, and lacks real-time visibility—leading to gaps in enforcement and accountability.

COSMOS: AI-Driven Monitoring Solution

COSMOS automatically identifies workers at designated exit points and detects unauthorized movement beyond operational zones. When a worker exits without approval, the system instantly generates an alert—complete with identity verification, video evidence, and a dashboard notification for supervisor validation. COSMOS also handles partial face occlusion from helmets and safety glasses while maintaining accurate identification. A fully automated registration process streamlines onboarding—simply uploading a photo triggers detection, alignment, and identity encoding. A built-in deduplication mechanism also prevents repeated alerts for the same individual, reducing noise and improving usability.

Built for Edge Performance

COSMOS runs multiple NVIDIA TensorRT FP16 inference engines on a single GPU, delivering <50ms latency per frame for real-time detection. A proprietary two-pass pipeline first detects workers, then re-analyzes cropped regions at higher resolution—improving accuracy for smaller PPE items often missed by conventional models. Display and inference are decoupled, ensuring smooth video at full FPS while detection runs asynchronously. The system supports up to 8 concurrent camera streams, with GPU-accelerated processing for efficient performance on edge devices.

Scalable and Deployment-Ready

COSMOS stores violation events with snapshots in PostgreSQL and streams results via WebSocket to a React-based dashboard for real-time monitoring. Deployed via Docker with NVIDIA Container Toolkit, the solution runs efficiently on edge hardware with 8GB+ GPU VRAM.

Unauthorized Exit Monitoring