A study on intelligent traffic management using IoT for urban congestion control
Department of Computer Science Engineering, Government Polytechnic, Kudligi, Karnataka, India.
Research Article
World Journal of Advanced Research and Reviews, 2019, 01(03), 085-091
Publication history:
Received on 13 April 2019; Revised 25 April 2019; accepted on 29 April 2019
Abstract:
Intelligent Traffic Management Systems (ITMS) play a vital role in enhancing the efficiency, safety, and sustainability of urban transportation networks. The research explores the integration of artificial intelligence, IoT, and data analytics in traffic management, highlighting their impact on congestion reduction, accident prevention, and environmental sustainability. Additionally, it discusses the future directions and potential avenues for further research in this domain.A smart city must have an intelligence-based traffic management system for the movement of vehicles. Traffic jams and vehicle parking problems are the most dominant problems that arise with increasing vehicles. The development of cities into better and smarter cities is through effective management and better traffic planning. Developing countries adopt better technologies, like smart traffic management systems, to cope with traffic-related problems and efficiently handle the same. One effective solution to the traffic-related problems is the green corridor passage for emergency vehicles. However, the usual traffic is hampered when a green corridor is a setup. Detection of traffic congestion and managing the real-time traffic flow is the most challenging task because it needs integration of real-time traffic-related data with the traffic control system. Only when this is achieved, one can think of finding a solution for the clearance of any emergency vehicle.
Keywords:
Intelligent Traffic Management Systems; Traffic planning; Congestion reduction; Real-time traffic-related; urban transportation networks
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Copyright © 2019 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0