A Real-Time Driver Drowsiness Detection and Immutable Behavior Logging Framework Using Vision and Blockchain Technologies

Driver fatigue is a major contributor to road accidents worldwide. This paper presents a real-time system that detects drowsiness using facial landmark analysis and securely logs each event using blockchain technology. The system identifies signs of eye closure and yawning through geometric rules and triggers alerts while recording location and time data on a tamper-proof ledger. Designed to run on low-power devices, the approach avoids the complexity of deep learning and ensures efficient, reliable performance. The integration of secure logging with real-time detection offers a practical solution for enhancing driver safety and accountability.