Work

Traffic Vehicle Monitoring System Using CNN

Year: 2025

Type: article

Abstract: Helmet violations and triple riding are major causes of road accidents. Manual enforcement is inefficient, requiring automation for better compliance. This project utilizes YOLO v8, OpenCV, and Tkinter to detect motorcycles, riders, and helmets from video frames. It identifies helmet absence and triple riding, displaying results via a user-friendly GUI. The system enhances real-time traffic monitoring, reducing manual effort and improving road safety.

Source: International Journal for Research in Applied Science and Engineering Technology

DOI: 10.22214/ijraset.2025.67656

Author: Prof. Aniket Gunjal

Institution: Zeal College of Engineering and Research, Pune

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4408850093

FWCI:

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