Real-Time Drowsiness Detection System for Driver Monitoring

Author:

Arunasalam M,Yaakob N,Amir A.,Elshaikh M,Azahar N F

Abstract

Abstract Nowadays, the rate of road accidents due to microsleep has been alarming. During microsleep, people might doze off without realizing it. For many decades, drowsiness detection system for vehicles was not among the major concerns though it turns out as one of imperative features that could have avoid microsleep and thus should be implemented in all vehicles in order to ensure safety of drivers and other vehicles on the road. To the best of our knowledge, enforcements on driving restriction during drowsiness state is yet to be implemented. The absence of such system in the current transportation systems expose drivers to great danger especially at night because accidents are highly likely to happen at night due to drowsy and fatigue drivers. Therefore, this project proposes a real-time drowsiness detection system for vehicles, featuring ignition lock to reduce accidents. An eye blink sensor is embedded in a wearable glasses and heart beat sensor is used to detect drowsiness level of drivers. The system also includes SMS notification system to relatives or friends with location details of the drowsy driver. This project is able to detect and react based on 3 levels of drowsiness by alerting the driver through buzzer. Ignition lock will be applied when high level of drowsiness is detected. Consequently, the vehicle will be slowed down and eventually stopped when dangerous level of drowsiness is detected as a safety precaution.

Publisher

IOP Publishing

Subject

General Medicine

Reference15 articles.

1. Development of an efficient system for vehicle accident warning;Rizwan,2013

2. Driver Drowsiness Detection Based on Time Series Analysis of Steering Wheel Angular Velocity;Gao,2017

3. Driver Drowsiness Detection Using Eye-Closeness Detection;Khunpisuth,2016

4. A driver face monitoring system for fatigue and distraction detection;Sigari;Int. Journal of Vehicular Technology,2013

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Smart Road Safety: An IoT Approach to Driver Drowsiness Detection and Prevention;Convergence of Machine Learning and IoT for Enabling the Future of Intelligent Systems;2024

2. Development of a Driver Detection System for Somnolence and Alertness Based on Image Processing Techniques;Applied Problems Solved by Information Technology and Software;2024

3. Drowsiness detection using Dlib: an overview;2023 7th IEEE Congress on Information Science and Technology (CiSt);2023-12-16

4. How to Prevent Drivers before Their Sleepiness Using Deep Learning-Based Approach;Electronics;2023-02-15

5. Survey on Driver Fatigue Detection Using Sensors, Big Data Analytics and Machine Learning Techniques;ICT with Intelligent Applications;2022-10-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3