ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

DRIVER DROWSINESS ALERT DETECTION FOR VEHICLEACCELERATION USING DEEP LEARNING 

Abstract

Abstract: Because of their hectic schedules, many people find it difficult to unwind and get a decent night's sleep at night.Drivers who are sleep deprived are more likely to fall asleep behind the wheel, increasing the likelihood of an accident. Thedriver assistance system is presented in this system with the goal of reducing the frequency of accidents caused by driverfatigue and thereby improving road safety. Based on optical information and artificial intelligence, this system treats theautomatic identification of facial and driver fatigue. We estimate distance between eye iris and neck angle by locating,tracking, and analysing both the driver's face and eyes. You can determine if a driver isn't paying attention in two ways: Ifyou can see the driver's face, you can know if the car is his or hers. The location of the eye and neck, as well as the activitiesof those being seen, are all taken into account. It is used to determine how far the eye iris angle is from the neck angle in theeye and neck angle-based approach. We are able to do so because we can deliver low-cost technologies to individuals. 

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Paper Submission Open For April  20212
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Last date for paper submission 30th April, 2022
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