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Safety Measure Detection Using Deep Learning

Author

Listed:
  • Tejas Bagthaliya
  • Vaidehi Shah
  • Shubham Shelke
  • Devang Shukla
  • Yatin Shukla

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.

Suggested Citation

  • Tejas Bagthaliya & Vaidehi Shah & Shubham Shelke & Devang Shukla & Yatin Shukla, 2024. "Safety Measure Detection Using Deep Learning," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(2), pages 148-155, April.
    • Handle: RePEc:jbh:ijsrcs:v10:y2024:i2:id:20
    DOI: 10.32628/CSEIT2490216
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2490216
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