Paper Key : IRJ************636
Author: Sonali Biradar,Shruti Pathak,Nikita Shirude ,Priya Tiwari ,Prof. Uma Patil
Date Published: 02 Apr 2025
Abstract
Now a days, in this modern growing world, accidents have become a major problem. Driver drowsiness is a critical concern in road safety, as it significantly contributes to traffic accidents and fatalities. This survey reviews advancements detection techniques using machine learning techniques, with a focus on using eye movement analysis. The proposed method incorporates the Haar Cascade Classifier to accurately classify the driver's state-alert or drowsybased on these eye metrics that is blink rate. This research highlights the potential of utilizing cascade classifiers in driver monitoring systems. This study helps in creating better systems to assist drivers and improve safety that can alert drivers in real-time, enhancing road safety and reducing accidents caused by drowsiness and drivers vigilance.
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