Measuring of Real-Time Traffic Flow Using Video from Multiple IP-Based Cameras

Mutharpavalar, A.A.P. and Sebastian, P. (2019) Measuring of Real-Time Traffic Flow Using Video from Multiple IP-Based Cameras. In: UNSPECIFIED.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Developing an intelligent transportation system that contains the basic information of the real-time traffic flow helps Lembaga Lebuhraya Malaysia to monitor and manage the traffic flow of our country. The main purpose of this paper is to detect and count vehicles along with its direction either towards North or South in real-time traffic flow by using multiple IP-based cameras. Open Source Computer Vision Library (OpenCV) and Python Programming language is used to implement the method developed. The project also provides an improvement by developing the system to be implemented in multiple cameras for real-time traffic measurement. The number of vehicles and their directions which are the output of the developed system is stored in json file to keep track of the data as well as the name of cameras with the time it is processed. The system developed is hoped to be a starting point in developing a more complex system. © 2019 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 1; Conference of 2019 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2019 ; Conference Date: 17 September 2019 Through 19 September 2019; Conference Code:157352
Uncontrolled Keywords: Cameras; Computer programming; Image processing; Information management; Intelligent systems; Open source software; Traffic signals, Computer vision library; Intelligent transportation systems; Keep track of; Multiple cameras; Number of vehicles; Python programming language; Real time traffics; Real-time traffic measurements, Advanced traveler information systems
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:25
Last Modified: 10 Nov 2023 03:25
URI: https://khub.utp.edu.my/scholars/id/eprint/11324

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