RoadSafe AI: Helmet and License Plate Detection Using Deep Learning

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

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-04-07
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.40819
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

RoadSafe AI: Helmet and License Plate Detection Using Deep Learning

K. Rajeswari, Jahnavi Lothugedda
International Journal For Multidisciplinary Research
Advanced Neural Network Applications
article

RoadSafe AI: Helmet and License Plate Detection Using Deep Learning

K. Rajeswari, Jahnavi Lothugedda
article en

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.

International Journal For Multidisciplinary ResearchVol. 7(2)
Openalex Percentile: Top 95%
Advanced Neural Network Applications
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