Fernando Fabian@williamffabian476572

VigiAI is an intelligent real-time surveillance system for detecting traffic accidents and anomalies. Running on an AMD MI300X accelerator, its hybrid architecture splits tasks between local processing—using Qwen-VL 7B, YOLO v8x, optical flow, and pose estimation—and cloud analytics via DeepSeek-V4 Flash through the Fireworks AI API. To handle chaotic real-world events, it was trained on the complete UCF-Crimes dataset (over 100 GB of footage). The system processes video through a structured 7-phase pipeline: Event Detection: Identifies anomalies instantly. Localization: Pins down spatial bounding boxes and timestamps. Scene Analysis: Evaluates weather, road, and lighting conditions. Causal Inference: Infers accident causes and secondary risks. Object Tracking: Tracks and counts vehicles or pedestrians. Speed Estimation: Measures velocity using pixel-to-meter calibration. Narrative Generation: Compiles an executive summary and detailed report. VigiAI detects 14 anomaly classes (accidents, theft, fights, fires, etc.) and transmits instant alerts via WebSockets over a public Cloudflare Tunnel. The web dashboard features live camera/webcam feeds, a GPS map, historical logs, and local vs. cloud performance metrics.

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