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@article{185991,
author = {D Rithika and Neetu Bala and Akansha Sing and Vaishnavi Singh},
title = {Smart Traffic Congestion Control Using IoT and Sensor Networks},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {12},
number = {5},
pages = {3551-3558},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=185991},
abstract = {Smart Traffic Congestion Control Using IoT and Sensor Networks Urban traffic congestion continues to be one of the largest issues in current transportation systems, resulting in delays, fuel loss, and greater environment pollution. With the recent growth of Internet of Things (IoT) and Wireless Sensor Networks (WSNs), intelligent traffic management systems that can perform real-time monitoring, forecasting, and control of congestion are possible. Here, we introduce a Smart Traffic Congestion Control System utilizing IoT-enabled WSNs with efficient data acquisition and intelligent control. Expanding from current structures like IoT-linked WSN-based traffic congestion control and data congestion control of intelligent transportation systems, we integrate real-time sensor data with adaptive routing and intelligent algorithms and optimize traffic with fewer bottlenecks. Providing vehicle-to-infrastructure (V2I) communication and dynamic congestion prediction, the system boosts road safety and travel time reduction and fosters urban sustainability. Simulation and analytical results show IoT-driven congestion control mechanisms outperform traditional methods with improved traffic efficiency and demonstrate their promise as future transportation infrastructures of smart cities.},
keywords = {Smart Transportation Systems; Internet of Things (IoT); Wireless Sensor Networks (WSN); Intelligent Traffic Management; Traffic Congestion Control; Data Congestion Framework; Vehicle-to-Infrastructure (V2I); Smart Cities; Real-Time Monitoring; Sustainable Mobility},
month = {October},
}
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