Hobbyist Builds Edge-AI Pan-Tilt Camera That Autonomously Tracks People

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A developer has built Netra, a self-tracking surveillance camera system that combines an ESP32-CAM, a YOLOv8 Nano object detection model, and servo motors to physically follow a detected person within the frame. The project originated as a microprocessors course assignment and evolved into a full edge-to-cloud stack coordinated over MQTT. Smooth tracking is achieved through proportional servo control and a 12% dead zone that prevents the camera from jittering in response to minor positional noise. A React dashboard supports manual, autonomous, and patrol operating modes for flexible deployment. The system also includes a behavioral anomaly layer called BASE, which applies time-weighted scoring to distinguish routine movement from potentially suspicious activity rather than triggering alerts on every detection.

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