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Intelligent Traffic Light Control Using IoT
Subject area: Science,Engineering and Technology · Area of research: IoT
Abstract
Urban population expansion has resulted in an unparalleled need for effective traffic control solutions. Even while they can be somewhat successful, traditional traffic signal management systems frequently fall short of dynamically adapting to the constantly shifting traffic circumstances, which leads to ongoing congestion, longer travel times, and environmental damage. In order to usher in an era of Intelligent Traffic Light Control, this study analyzes a revolutionary method that involves integrating the Internet of Things (IoT) with traffic light control systems. The management of traffic flow in cities and regions can undergo a paradigm change thanks to the Internet of Things' pervasive connection and data-driven insights.
Keywords
IoT, Traffic Management, Safety, City Planning, Transportation
References
[1] Kumar, N. Dinesh, G. Bharagava Sai, and K. Shiva Kumar. "Traffic control system using labview." Vol2-Issue2-2013 (2013).
[2] Thatsanavipas, K., et al. "Wireless traffic light controller." Procedia Engineering 8 (2011): 190-194.
[3] Ma, Wanjing, and Xiaoguang Yang. "Design and evaluation of an adaptive bus signal priority system base on wireless sensor network." 2008 11th International IEEE Conference on Intelligent Transportation Systems. IEEE, 2008.
[4] Shimizu, Hikaru, et al. "A development of deterministic signal control system in urban road networks." 2008 SICE Annual Conference. IEEE, 2008.
[5] Weil, Roark, J. Wootton, and A. Garcia-Ortiz. "Traffic incident detection: Sensors and algorithms." Mathematical and computer modelling 27.9-11 (1998): 257-291.
[6] George, Anna Merine, V. I. George, and Mary Ann George. "IoT based smart traffic light control system." 2018 International conference on control, power, communication and computing technologies (ICCPCCT). IEEE, 2018.
[7] Dilip, B., Y. Alekhya, and P. Divya Bharathi. "FPGA implementation of an advanced traffic light controller using Verilog HDL." International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) 1.7 (2012): 2278-1323.
[8] Abbas, Aymen Fadhil, et al. "A comprehensive review of vehicle detection using computer vision." TELKOMNIKA (Telecommunication Computing Electronics and Control) 19.3 (2021): 838-850.
[9] Udofia, Kingsley Monday, Joy Omoavowere Emagbetere, and Frederick Obataimen Edeko. "Dynamic traffic signal phase sequencing for an isolated intersection using ANFIS." Automation, Control and Intelligent Systems 2.2 (2014): 21- 26.
[10] Dong, Hao, Xingguo Xiong, and Xuan Zhang. "Design and implementation of a real-time traffic light control system based on FPGA." Proceeding of the 1st Conference on ASEE. 2014.
[11] Zhou, Binbin, et al. "Adaptive traffic light control in wireless sensor network-based intelligent transportation system." 2010 IEEE 72nd Vehicular technology conference-fall. IEEE, 2010.
[12] science and engineering technology. 2022;10(11):1374-7.
[13] Albadawi Y, AlRedhaei A, Takruri M. Real-time machine learning-based driver drowsiness detection using visual features. Journal of imaging. 2023 Apr 29;9(5):91.
[14] Raghu N, Deekshith P, Kumar PP. Driver Drowsiness Detection System using CNN.
How to cite this paper
@article{1705464,
author = {Harsh Anavkar, Rahul Yadav, Santosh Singh, Mithilesh Vishvakarma},
title = {Intelligent Traffic Light Control Using IoT},
journal = {Iconic Research And Engineering Journals},
year = {2024},
volume = {7},
number = {8},
pages = {46-51},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1705464.pdf},
abstract = {Urban population expansion has resulted in an unparalleled need for effective traffic control solutions. Even while they can be somewhat successful, traditional traffic signal management systems frequently fall short of dynamically adapting to the constantly shifting traffic circumstances, which leads to ongoing congestion, longer travel times, and environmental damage. In order to usher in an era of Intelligent Traffic Light Control, this study analyzes a revolutionary method that involves integrating the Internet of Things (IoT) with traffic light control systems. The management of traffic flow in cities and regions can undergo a paradigm change thanks to the Internet of Things' pervasive connection and data-driven insights.},
keywords = {IoT, Traffic Management, Safety, City Planning, Transportation},
month = {February},
}