Design and Implementation of an IoT Drowsiness Detection System for Drivers

Author:

KALLEL Fathi1

Affiliation:

1. Sfax University

Abstract

Abstract Drowsiness stands as a significant peril to road safety, manifesting as a prominent contributor to severe injuries, fatalities, and substantial economic ramifications within the realm of road accidents. The presence of drowsiness substantially diminishes driving performance, fostering a decline in attentiveness and reaction times. This, in turn, exacerbates the potential for accidents and underscores the criticality of addressing drowsiness-related issues to mitigate the adverse consequences on road safety. The objective of this research work is to design and implement an IoT based intelligent alert system for vehicles, capable of automatically mitigating the risks associated with drowsy driving. Indeed, we propose a real time drowsy driver alert system including a hardware and a software parts. The hardware part includes a camera for face image acquisition and a Raspberry Pi 4 platform for real time face image processing to analyze eye blinks and drowsiness detection. The software part includes a web application for drivers’ management and a mobile application for drowsiness detection and notification management. In fact, once the driver's drowsiness is detected, the system instantaneously sends all details to a wireless connected real-time database and the mobile application module issues a warning message, while a Raspberry Pi monitoring system delivers an audible alert to the driver.

Publisher

Research Square Platform LLC

Reference27 articles.

1. Hash-chain-based IoT authentication scheme suitable for small and medium enterprises;Jeong YS;J. Converg Inf. Technol.,2017

2. Azmat, M., Kummer, S., Moura, L.T., Gennaro, F.D., Moser, R.: Future Outlook of Highway Operations with Implementation of Innovative Technologies Like AV, CV, IoT and Big Data, vol. 3, p. 15. Logistics (2019)

3. Wintersberger, S., Azmat, M., Kummer, S.: AreWe Ready to Ride Autonomous Vehicles? A Pilot Study on Austrian Consumers’ Perspective. Logistics 3, 20. (2019)

4. Eye Detection in Facial Images Using Zernike Moments with SVM;Kim JH;ETRI J.,2008

5. Potential applications of unmanned ground and aerial vehicles to mitigate challenges of transport and logistics-related critical success factors in the humanitarian supply chain;Azmat M;AJSSR,2020

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