Real Time Traffic Signal Optimization and Vehicle Surveillance Using Deep Learning

Mohammad Fathimunnisa, Vemula Deepthi, L. Sandhya Rekha, Anumula Pavithra, Takkasheela Archana

2025

Abstract

In the modern scenario wherein, traffic congestion and poor signal management are the serious concerns of cities, there is a demand for best-in-class solutions for its real-time optimization. This paper proposes a traffic signal control and vehicle detection system based on deep learning with CNN and object detection. It automatically adjusts signal times based on traffic density and reduces jams and optimizes road traffic. The detection of traffic offenses and observation of road activity further augment surveillance. Its method offers better accuracy, reduced waiting time and increased flexibility compared to the traditional methods. Experimental results confirm the system's effectiveness for optimal urban traffic management with prompt decision-making. Using AI-based strategies together can ensure a hyper-efficient, scalable solution to Transportation needs’ in the new age.

Paper Citation

in Harvard Style

Fathimunnisa M., Deepthi V., Rekha L., Pavithra A. and Archana T. (2025). Real Time Traffic Signal Optimization and Vehicle Surveillance Using Deep Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 51-55. DOI: 10.5220/0013922400004919

in Bibtex Style

@conference{icrdicct`2525,
author={Mohammad Fathimunnisa and Vemula Deepthi and L. Rekha and Anumula Pavithra and Takkasheela Archana},
title={Real Time Traffic Signal Optimization and Vehicle Surveillance Using Deep Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={51-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013922400004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Real Time Traffic Signal Optimization and Vehicle Surveillance Using Deep Learning
SN - 978-989-758-777-1
AU - Fathimunnisa M.
AU - Deepthi V.
AU - Rekha L.
AU - Pavithra A.
AU - Archana T.
PY - 2025
SP - 51
EP - 55
DO - 10.5220/0013922400004919
PB - SciTePress