Intelligent Traffic Signaling Using IoT: A Real-Time Solution for Congestion in Urban Areas
- DOI
- 10.2991/978-94-6239-693-7_33How to use a DOI?
- Keywords
- Internet of Things; IR sensor; gas sensor; Dynamic traffic signaling; air pollution detection
- Abstract
Rapid urbanization has made significant changes and challenges to traffic systems. Increased vehicle usage in the metropolitan regions has resulted in the surge in roadway crowding and pollution near junctions, as the traffic signals are predetermined without considering the levels of congestion. This proposed work presents an IoT-assisted signal management system. The Infrared (IR) sensors placed along these intersecting roadways are utilized to identify the existence of vehicles and dynamically adjust the traffic release time accordingly. Additionally, the gas sensor detects the pollutant levels in the surroundings which helps in environmental monitoring. This dual focus approach ensures smoother flow of traffic along with promoting environmental health monitoring. This system also proposes a low-cost solution for dynamic traffic signaling using IR sensors. Unlike existing systems that only concentrate on traffic signaling or environment monitoring, this system focuses on both congestion control and air quality monitoring in a cost-effective manner.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Atluri Aasritha AU - Golve Anusha AU - Reshmitha Kilaru AU - D. Rajeswara Rao PY - 2026 DA - 2026/06/16 TI - Intelligent Traffic Signaling Using IoT: A Real-Time Solution for Congestion in Urban Areas BT - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026) PB - Atlantis Press SP - 329 EP - 337 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6239-693-7_33 DO - 10.2991/978-94-6239-693-7_33 ID - Aasritha2026 ER -