Issue |
E3S Web Conf.
Volume 309, 2021
3rd International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2021)
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Article Number | 01099 | |
Number of page(s) | 5 | |
DOI | https://doi.org/10.1051/e3sconf/202130901099 | |
Published online | 07 October 2021 |
New Directions in Traffic Control Analysis through Video Surveillance
1, 2, 4 Department of C. S. E, Aditya College of Engineering & Technology, Surampalem.
3 Department of C. S. E, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad
5 Ivy Comptech Pvt ltd., Hyderabad.
* Corresponding author: rvslalitha@gmail.com
Traffic management is an increasing problem in both cities and sub urban areas. Authority people involved in traffic management system spend much of time in controlling traffic at junctions. With the advances in technology, monitoring traffic through image processing and video surveillance techniques became the researchers’ attention. These techniques help us in controlling traffic as well as to identification of kamikaze drivers and speed violators. The key focus of this research is to do traffic analysis using video surveillance to detect speedy drivers. A wide range of traffic parameters such as flow of traffic, speed of vehicles and vehicle registration number are the major components involved in this research. In this paper, traffic analysis is carried out based on streaming video data with YOLO tool. In this paper an eco system is developed for object detection, vehicle number detection and the speed of the vehicle using computer vision algorithms. With the application tool developed, traffic control authority people can warn the speedy drivers on the fly.
Key words: YOLO tool / Object detection / Video streaming / Classification / ALPR
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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