OT Sentinel Edge AI

OT Sentinel Edge AI is a cyber-physical resilience platform for industrial and operational environments. It turns live camera, video, and sensor signals into explainable operational intelligence at the edge, helping teams detect unsafe conditions, equipment anomalies, suspicious activity, and emerging incidents before they become major disruptions. The prototype uses computer-vision inference with OpenVINO and ONNX models to process real-world inputs locally, reducing latency and unnecessary cloud exposure. Detected events are correlated with operational context to estimate affected assets and blast radius. A governed decision layer then recommends containment or remediation actions, but keeps high-impact actions behind explicit human approval. The system is designed around production concerns rather than a single model demo: edge inference, evidence capture, event severity, confidence scoring, auditability, human-in-the-loop controls, and post-action verification. A web dashboard presents live detections, incident timelines, affected assets, recommended actions, and evidence. For the AI Infra Summit Hackathon, the focus is demonstrating how Intel-aligned edge AI can move from perception to a safe, explainable operational response using a standard webcam/video feed and an industrial monitoring scenario. The longer-term goal is a deployable platform for factories, utilities, data centres, logistics sites, and other environments where physical operations and cybersecurity increasingly overlap.