Artificial Intelligence Software Application for Contactless Traffic Violation Apprehension in the Philippines

Author:

Jose John Anthony C., ,Billones Jr. Ciprian D.,Brillantes Allysa Kate M.,Billones Robert Kerwin C.,Sybingco Edwin,Dadios Elmer P.,Fillone Alexis M.,Lim Laurence A. Gan

Abstract

This paper presents a prototype of a centralized contactless traffic violation apprehension system composed of an artificial intelligence (AI) engine and a web application. The AI engine collects traffic data, primarily traffic violation data, through a contactless approach by using different video and image processing techniques and AI algorithms in its three modules: license plate detection, optical character recognition (OCR), and number coding violation detection. The web application consolidates all the data produced by the AI engine and provides a graphical user interface (GUI) for data management, visualization, and analysis. This contactless apprehension system aims to automate, standardize, and streamline the existing processes of law enforcement agencies and institutions for a more efficient apprehension of traffic violators and help them improve their traffic planning and management in the congested areas of the Philippines.

Funder

Philippine Council for Industry, Energy, and Emerging Technology Research and Development

De La Salle University

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference20 articles.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing Urban Traffic Management: Advanced Strategies in Image Recognition-Based Intelligent Traffic Monitoring;Traitement du Signal;2023-12-30

2. License Plate Recognition System for Improved Logistics Delivery in a Supply Chain with Solution Validation through Digital Twin Modeling;2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM);2023-11-19

3. Method For Traffic Violation Detection Using Deep Learning;2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS);2023-11-07

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