Internet of Things-Based Smart Traffic Light System for Hassle Free Movement of Emergency Vehicles

Author:

S. Muthurajkumar1ORCID,V. K. Danush Gupta1,Vijjappu Parvatheeswara Siddharth Gupta2

Affiliation:

1. Anna University, Chennai, India

2. Viterbi School of Engineering, University of Southern California, USA

Abstract

Given the increasing number of vehicles on the road, the intensity of vehicular traffic in cities has tremendously increased. Because of the heavy traffic, there are often traffic delays on the roads, which can result in the loss of human life when emergency medical vehicles like ambulances and fire engines are stuck in the traffic jam. Traffic congestion is thought to be responsible for 30-35% of mortality in emergency situations, according to data compiled from various sources. In such conditions, it becomes essential that the traffic keeps flowing at a faster rate but in a smooth manner. The authors have devised a strategy to cut the amount of time an emergency vehicle spends at signal stops and the amount of manpower required at each traffic signal. The project's primary objective is to use IoT sensors to detect the arrival of emergency vehicles and reduce the time it takes for the vehicle to pass the traffic lights by favouring the lane in which the emergency vehicle is detected by turning traffic lights green to allow other vehicles in front to give way to the emergency vehicle.

Publisher

IGI Global

Reference27 articles.

1. Intelligent traffic control system for smart ambulance.;D.Ahir;IRJET,2018

2. STLS: Smart Traffic Lights System for Emergency Response Vehicles

3. IoT based Intelligent Traffic Signal System for Emergency vehicles

4. Recognition of Emergency Vehicle Using Light Detection and Traffic Light Controlling. International Research;Gowtham;Journal of Engineering Technology,2021

5. Low cost traffic control system for emergency vehicles using ZigBee

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