Year: 2025
Type: article
Abstract: This study presents the Helmet and License Plate Detection system, which leverages deep learning techniques to enhance road safety and streamline law enforcement. The system provides an intuitive interface that allows users to upload images, where it processes the content to determine whether the motorcyclist is wearing a helmet and recognizes the vehicle’s license plate. Using Convolutional Neural Networks (CNNs), the helmet detection module analyzes the uploaded image to detect the presence or absence of a helmet on the rider. If no helmet is detected, the system automatically extracts the vehicle's license plate using Optical Character Recognition (OCR) and alerts the appropriate authorities. In addition, the system triggers an email notification, providing real-time updates for law enforcement or traffic management. This dual functionality of helmet detection and license plate recognition offers a comprehensive solution for enhancing public safety, ensuring compliance with helmet laws, and assisting in the efficient tracking of vehicles. The integration of these features into one platform could improve road safety, reduce traffic violations, and enable more effective law enforcement by providing timely, actionable data. The system is designed to be scalable and can be deployed in various settings, including traffic surveillance, smart cities, and security systems.
Authors: Jahnavi Lothugedda, Rajeswari K
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409212904