International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI Helmet Detection |
|---|---|
| ABSTRACT | Skin lesion classification is the first and necessary step toward early detection of dermatological conditions, especially melanoma, responsible for the vast majority of skin cancer-Abstract—Helmet Detection using Artificial Intelligence (AI) is an advanced approach designed to improve road safety by identifying riders who are not wearing helmets. With the rapid increase in road traffic and the limitations of manual surveillance, an automated solution is essential. This research explores a deep learning-based helmet detection framework designed to work with real-time traffic surveillance systems. The system employs computer vision techniques, particularly YOLO-based object detection models, to classify whether motorcyclists are helmeted or non-helmeted. Experimental results demonstrate high accuracy across varied lighting, angles, and traffic densities. The findings indicate that AI-driven helmet detection can significantly enhance traffic law enforcement and reduce accident-related injuries. |
| AUTHOR | PROF. N THANUJA, VEVOTO NYEKHA, DILER SINGH YADAV Department of Computer Science and Engineering, Bangalore Institute of Technology, Bangalore, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312138 |
| pdf/138_AI Helmet Detection..pdf | |
| KEYWORDS | |
| References | [1] Ayyoub Bouhayane, Zakaria Charouh, Zouhair Guennoun, “A Swin Transformer-Based Approach for Motorcycle Helmet Detection”, 2023. [2] Shun Cui, Tiantian Zhang, Hao Sun, Xuyang Zhou, “An Effective Motorcycle Helmet Object Detection Framework for Intelligent Traffic Safety”, 2023. [3] Zhaozhang OuYang, Jeffrey S. Sarmiento, “Detection of Motorcycle Helmet Wearing in Complex Traffic Environments Based on YOLOv8”, 2024. [4] Drisya C, Leena Mary, “Detection of Motorcyclists Without Helmet from Traffic Video Using Deep Learning Techniques”, 2022. [5] Hanhe Lin, Deike Albers, Jeremiah, “Helmet Use Detection of Tracked Motorcycles Using CNN-Based Multi-Task Learning” ,2020. [6] Saravit Soeng, WanSup Cho, Jae-Sung Kim, “Automated Detection of Motorcycle Rider Without Wearing Helmet Using Surveillance Camera”, 2024. [7] Uday Bhaskar Voora, Prajwala T R, “Helmet Violation and Number Plate Detection System”, 2023. [8] Manjesh N Shetty, “Smart Helmet Using GSM & GPS Technology for Accident Detection and Reporting System”, 2024. [9] Julie Ann B. Susa, Carla May C. Ceribo, “An Efficient Safety and Authorized Helmet Detection Using Deep Learning Approach”, 2022. [10] Ashwin Dhakal, Bijaya Hatuwal, “Real-Time Helmet Violation Detection in AI City Challenge 2023 with Genetic Algorithm-EnhancedYOLOv5”,2023 |
