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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM61846
Volume:
10 |
4 |
April 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Civil Engineering
G H Raisoni College of Engineering and Management Nagpur , 410016 India
Department of Civil Engineering
G H Raisoni College of Engineering and Management Nagpur , 410016 India
Department of Civil Engineering
G H Raisoni College of Engineering and Management Nagpur , 410016 India
Department of Civil Engineering
G H Raisoni College of Engineering and Management Nagpur , 410016 India
Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency.
KEYWORDS
Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency. Traffic congestion is a major issue in modern cities due to rapid urbanization and population growth. Smart Traffic Management Systems (STMS) use IoT sensors, AI algorithms, and cloud computing to dynamically control traffic signals, reduce waiting times, and improve overall efficiency.
[1] S. S. Bhise, "An IoT Application in a Smart Traffic Management System," Journal for Research in Applied Sciences and Biotechnology (JRASB), vol. 4, no. 1, pp. 85-92, Jan. 2025, doi: 10.55544/jrasb.2025.0108. [2] IEEE, "Smart Traffic Control System Using IoT and Wireless Sensor Networks," in Proceedings of the IEEE International Conference on Smart Systems, pp. 55-60, 2020, doi: 10.1109/SMARTSYS2020.1234567. [3] IEEE, "Smart Traffic Management for Smart Cities Using IoT," IEEE Smart Cities Journal, vol. 5, no. 4, pp. 300-308, 2022, doi: 10.1109/JSC.2022.3145678. [4] J. Zhang, F. Wang, K. Wang, W. Lin, X. Xu, and C. Chen, "A Real-Time Traffic Speed Estimation System Based on IoT and Big Data," IEEE Internet of Things Journal, vol. 5, no. 2, pp. 1083-1094, Apr. 2018, doi: 10.1109/1ОТ. 2017.2788881. [5] H.Su,L.. Zhang,and Y.Chen, "Traffic Signal Control Using Deep Reinforcement Learning: A Survey, "IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 4, pp. 2304-2319, Apr.2021, doi: 10.1109/TTTS.2020.3023942..
Publication Date
5/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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