OPTIMIZATION OF REAL TIME DRIVER FATIGUE DETECTION AND ALERT SYSTEM USING ARDUINO NAN

Abstract

Driver fatigue is a major factor contributing to road accidents, particularly during long-distance and nighttime driving. Early indicators of drowsiness—such as extended eye closure or a reduced blink rate—often go undetected by drivers, significantly raising the risk of collisions. This paper presents a real-time, cost-effective driver drowsiness detection and alert system built around the Arduino Nano microcontroller and an infrared (IR) eye blink sensor. Unlike traditional approaches that rely on camera-based systems or complex physiological monitoring, this solution is designed to be simple, non-intrusive, and reliable across a range of lighting conditions. The IR sensor functions by detecting eye closure through reflected infrared light, and activates a buzzer alert when the eyes remain closed beyond a set threshold. The Arduino Nano ensures fast processing, seamless integration, and low power consumption, making the system ideal for both private and commercial vehicles—particularly in developing areas where access to advanced driver-assistance systems (ADAS) is limited. The prototype has been thoroughly tested across different environmental settings and user profiles, proving its accuracy and robustness. This paper details the system’s design, functionality, and testing, while also exploring its potential for future enhancements, such as incorporating AI for smarter fatigue detection and telematics integration. Overall, the proposed system offers an accessible, scalable, and effective solution to improve road safety and mitigate fatigue-related accidents.