Paper Key : IRJ************151
Author: Jagrut M. Thakare,Yogesh P. Bawankar,Atharva Ravindra Bhuyar,Sarang V. Khode,Tanuja M. Deshpande,Ashwini P. Ghatol
Date Published: 14 Apr 2025
Abstract
This paper provides a comprehensive review of hybrid traffic safety systems that integrate Automatic Number Plate Recognition (ANPR) with Helmet Detection and Triple Ride Detection technologies. As urbanization increases, so does the complexity of traffic management, necessitating advanced solutions to ensure road safety. Traditional ANPR systems, while effective in vehicle identification, often fail to address critical safety issues such as helmet compliance and the detection of multiple riders on motorcycles. This review examines recent advancements in these integrated systems, highlighting their potential to enhance traffic law enforcement by ensuring compliance with safety regulations. The paper discusses the strengths and limitations of current methodologies, particularly in real-time processing and accuracy under varying conditions. Furthermore, it proposes a framework that leverages deep learning models, such as YOLOv2 and EasyOCR, to improve detection efficiency and reliability. The integration of these technologies offers a holistic approach to traffic monitoring, with the potential to significantly reduce traffic violations and accidents. Future research directions are also suggested to address existing challenges and enhance the scalability and effectiveness of these systems.
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