Edge-AI Driver Drowsiness & Distraction Telemetry on Jetson Nano / ESP32-CAM
Real-time edge vision system calculating Eye Aspect Ratio (EAR) and head pose angles at 30 FPS to trigger instant cabin buzzer alarms.
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Project Technical Overview
Deploys an optimized MobileNetV3 and facial landmark detector onto edge hardware (NVIDIA Jetson / Raspberry Pi). Computes real-time PERCLOS (percentage of eyelid closure), yawning frequency, and phone distraction, sounding alerts before micro-sleep accidents occur.
Read the foundational IEEE conference research paper, citations, and algorithmic architecture for this project.