Paper Key : IRJ************014
Author: Aman Najeer Chougule,Ashwinkumar Mukund Dalavi,Amit Sharad Patil,Sarthak Mhalappa Pujari,Ms.s.s.gadkari
Date Published: 04 Mar 2024
Abstract
Drunk driving is a widespread problem that causes thousands of fatal collisions every year. Over the past ten years, there have been continuous advancements in computer technology and artificial intelligence, which have enhanced driver monitoring systems. A number of experimental studies have collected real-world driver fatigue data, applied various artificial intelligence algorithms, and integrated features in an attempt to significantly enhance the efficiency of these systems. The proposed system aims to improve transportation safety by lowering the number of accidents brought on by tired and drowsy drivers. As a result, accidents have become more common in the recent past. Several facial expressions and physical gestures, like yawning and sleepy eyes, are thought to be signs of fatigue and drowsiness in drivers. We can also provide one alert message set at a particular time interval for the white-line fever prevention system. The study also examines the reliability and practicability of each of the four system types, highlights current issues in the field of driver drowsiness detection, and outlines some potential future directions.