SentinelVision Edge
Edge AI camera platform: Raspberry Pi nodes run YOLO detection and report occupancy over MQTT/WebSocket to a FastAPI + Vue control room with live MediaMTX streams.
Overview
SentinelVision Edge turns low-cost Raspberry Pi cameras into an AI security fleet. Node agents run YOLO person and face detection at the edge, publish occupancy and dwell-time signals over MQTT, and stream video through MediaMTX. A FastAPI backend with PostgreSQL, Redis and Celery manages cameras, areas, recordings and roles, with a Vue 3 dashboard for real-time status.
The challenge
Cameras sit on unreliable networks, and the control room must stay useful while nodes drop offline. Video streaming, AI inference and real-time reporting had to fit a Raspberry Pi thermal budget while RBAC, recording control and historical state stayed centralized.
Our solution
Split responsibilities deliberately: inference and occupancy logic on the node, video handled by MediaMTX, fleet state in a FastAPI backend with Celery workers. Real-time status flows over MQTT topics and WebSockets, and a domain-style agent layout (adapters/application/domain/infrastructure) keeps edge logic testable.
Key features
Results & impact
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SentinelVision Edge