IJAIEM

K.Sireesha, P.S.Afeena, M.Sumith Krishna, G.Revanth Kumar, P.Gayathri, S.Jayavardhan

Abstract

Road accidents caused by driver fatigue and inattentiveness remain a pressing concern, especially in countries like India. To mitigate such hazards, a robust Driver Drowsiness Detection and Accident Prevention System has been conceptualized. This solution employs Python-based image processing techniques to track the driver's eye aspect ratio in real time, offering continuous vigilance for early signs of drowsiness. The system is supported by an integrated hardware framework comprising two Arduino microcontrollers—one mounted on a robotic vehicle fitted with motors, ultrasonic sensors, and Bluetooth connectivity, while the second acts as a communication bridge between the software and vehicle. This intelligent blend of software analytics and embedded hardware provides an effective safety mechanism that can generate alerts and intervene when required. By proactively identifying driver fatigue and responding accordingly, the system aspires to minimize road mishaps and improve trav