Safety Measure Detection Using Deep Learning

Tejas Bagthaliya, Vaidehi Shah, Shubham Shelke, Devang Shukla and Yatin Shukla

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 2, 148-155

Abstract: This implementation is for a computer vision application that detects individuals and verifies their compliance with safety gear regulations, such as safety jackets and hard-hats. The system counts the number of individuals violating safety standards and keeps track of the total number of individuals detected. The system uses advanced image processing techniques, including object detection and classification, to accurately identify the presence or absence of safety gear. The user interface provides real-time analysis of the data, with the option to alert the user of any violations. This implementation is a valuable tool for organizations looking to ensure the safety of their employees and customers, providing a comprehensive solution for monitoring compliance with safety regulations. It can also be used to analyze trends and identify areas for improvement, making it an essential tool for safety professionals and facilities managers.

Keywords: Convolutional Neural Network; Deep Learning; Safety Measures; Object Detection; Image Classification (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2490216
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i2:id:20

DOI: 10.32628/CSEIT2490216

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