IoT based smart traffic signal monitoring system using vehicles counts

Author:

Kumar Janahan Senthil,R.M. Veeramanickam M,Arun S,Narayanan Kumar,Anandan R,Javed Parvez Shaik

Abstract

Traffic signal management is one of the major problematic issues in the current situation. Such scenarios, every signal are getting 60 seconds of timing on the road at a regular interval, even when traffic on that particular road is dense. As per this proposed model in this article, which will be optimized the timing interval of the traffic signal purely depends on the number of vehicles on that particular roadside. The major advantage of this system is that it can able to decrease the more waiting time for the drivers to cross road signal.  In this model, we are using the clustering algorithms model which is based on KNN algorithm. Using this algorithm new model will be liable to determine expected required timing as per provided inputs to the signal which is vehicles count. The input of these systems is vehicles counts on each side of the road from crossing signal.  And this input will be determined on much time is to be provided. “Case studies on this system are traffic network and real-time traffic sub-networks are organized to get the effectiveness of the proposed model.”  

Publisher

Science Publishing Corporation

Subject

Hardware and Architecture,General Engineering,General Chemical Engineering,Environmental Engineering,Computer Science (miscellaneous),Biotechnology

Cited by 31 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. Vision based intelligent traffic light management system using Faster R‐CNN;CAAI Transactions on Intelligence Technology;2024-04-10

2. Enhanced Vehicle Detection Mechanism for Traffic Management in Smart Cities;Wireless Personal Communications;2024-04

3. IOT based traffic light control based on traffic density;2023 Second International Conference on Informatics (ICI);2023-11-23

4. Traffic-free emergency health corridor;Scientific African;2023-11

5. Real-time traffic monitoring system using IoT-aided robotics and deep learning techniques;Kuwait Journal of Science;2023-11

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