EYES ON THE ROAD: A DUAL APPROACH TODETECTING DROWSINESS AND DISTRACTION

Abstract

Road safety has become a major concern due to the increasing number of accidents caused by
driver drowsiness and distraction. These two factors significantly reduce driver alertness,
reaction time, and decision-making ability, often leading to severe road incidents. The project
“Eyes on the Road: A Dual Approach to Detecting Drowsiness and Distraction” presents an
intelligent monitoring system designed to identify both driver fatigue and inattentive behavior
in real time. The main objective of this system is to enhance road safety by continuously
observing the driver’s facial and head movements and generating timely alerts whenever
unsafe conditions are detected.
The proposed system uses computer vision and artificial intelligence techniques to monitor
the driver through a camera installed inside the vehicle. For drowsiness detection, features
such as eye closure rate, blinking pattern, and yawning frequency are analyzed. If the driver’s
eyes remain closed for an unusual duration or repeated yawning is observed, the system
classifies the state as drowsy. For distraction detection, the model tracks head pose, gaze