Optimization of smart traffic management system using machine vision-based functionalities with CNN model

Varma, Surya Pratap Singh, Jaiswal, Aadrika, Das, Nirupam, Yang, Tiansheng, Sun, Ruikai and Rathore, Rajkumar Singh 2026. Optimization of smart traffic management system using machine vision-based functionalities with CNN model. Presented at: International Conference on Computing Systems and Intelligent Applications, Delhi, India, 28-29 March 2025. Published in: Jaiswal, Ajay, Anand, Sameer, Hassanien, Aboul Ella and Azar, Ahmad Taher eds. Proceedings of ComSIA 2025. Lecture Notes in Networks and Systems. Springer, pp. 317-327. 10.1007/978-981-96-8343-7_25

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Abstract

The rapid developing volume of urban activity has made an urgent need for smart arrangements to oversee congestion and improve road safety. This paper presents a Smart Traffic Management System (STMS) that utilizes computer vision to optimize real-time traffic flow. By analyzing live video streams from various traffic cameras, the system is able to evaluate vehicle congestion, classify different types of vehicles, and detect traffic violations. From the various application of methods such as object detection, motion tracking, and deep learning, the STMS alters traffic signals dynamically, making a difference to ease traffic congestion and improve traffic flow. Moreover the system can identify accidents and alarm the appropriate authorities to encourage convenient intervention. The system’s execution was tested over various urban conditions showing impressive advancements in both traffic management and traffic congestion reduction.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Business (Including Economics)
Publisher:	Springer
ISBN:	9789819683420
ISSN:	2367-3370
Last Modified:	12 Jan 2026 14:47
URI:	https://orca.cardiff.ac.uk/id/eprint/183806

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