Paper Title
Helmet Detection System using YOLOv5
Article Identifiers
: Keywords
Helmet detection,YOLOv5 model ,Deep learning,Real-time ,Object detection,Road safety,Neural network,Processing time ,Efficiency,Head injuries
Abstract
A helmet detection system is a computer vision technology that can be used to ensure the safety of workers in various industries where helmets are required, such as construction, mining, and transportation. The system uses artificial intelligence algorithms to analyze images or videos and identify the presence of a helmet based on its color, shape, and texture. The detection system can also differentiate between different types of helmets, such as hard hats and motorcycle helmets.The primary objective of a helmet detection system is to reduce the risk of accidents and injuries caused by workers not wearing helmets. This system provides real-time feedback to workers who are not wearing helmets, reminding them of the importance of wearing one, and ultimately leading to better compliance with safety regulations. Overall, a helmet detection system is an essential tool for ensuring the safety of workers in hazardous environments. It provides an automated and accurate method for detecting the presence of helmets, leading to better compliance with safety regulations and ultimately reducing the risk of accidents and injuries
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How To Cite (APA)
Vivek Shah, Saurav Pawar, Sahil Bashir Mohamed, Pranali Wagh, & Vaisali Korade (April-2023). Helmet Detection System using YOLOv5. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), h1-h4. https://ijnrd.org/papers/IJNRD2304700.pdf
Issue
Volume 8 Issue 4, April-2023
Pages : h1-h4
Other Publication Details
Paper Reg. ID: IJNRD_192833
Published Paper Id: IJNRD2304700
Downloads: 000122253
Research Area: Information TechnologyÂ
Author Type: Indian Author
Country: Thane, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2304700.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304700
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