Paper Contents
Abstract
Fatigue driving has emerged as one of the top causes of road accidents in the world, constituting a serious risk to transport safety. Prolonged hours of driving, repetitive routes, and lack of adequate rest are typical conditions that result in progressive reduction of driver vigilance. In contrast to external dangers like road conditions or mechanical issues, drowsiness builds up internally and frequently without immediate consciousness, which makes it especially risky. Therefore, there is an urgent need for systems that can detect signs of fatigue before they lead to fatal mistakes on the road. This paper presents a real-time vision-based drowsiness detection system that monitors facial behavior to detect early warning signs of tiredness
Copyright
Copyright © 2025 Jayshree M. Khairnar. This is an open access article distributed under the Creative Commons Attribution License.
