Real Time Driver Drowsiness Detection Using Arduino

Abstract

Driver fatigue plays a significant role in road accidents, particularly during long journeys or when traveling at night. Recognizing early signs of drowsiness can help prevent such incidents and improve overall road safety. In this work, a real-time driver drowsiness detection model is developed using computer vision techniques and embedded hardware. A camera monitors the driver’s eye activity, and when the eyes stay shut for over five seconds, the system identifies it as a sign of fatigue. Upon detection, the system initiates several responses: a beep is sounded through the laptop speaker, LED lights are activated via a microcontroller, and a motor-driven mechanism slows down the vehicle. The system uses open-source software and low-cost hardware components, making it practical for use in educational and prototype environments. It was tested across different users and lighting conditions, consistently detecting drowsiness and responding with minimal delay. The combination of real-time image processing and simple hardware control offers a reliable, affordable safety solution. With further improvements, such as head tracking or emergency alerts, the system may achieve greater robustness and adaptability. Overall, this paper demonstrates a feasible and scalable approach to preventing fatigue-related accidents using accessible technology.