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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Personal Protective Equipment detection in chemical industry |
| Authors Name: | Mohanraj S , Dineshkumar S , Kalaivani M , Monish S |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_194605
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| Published Paper Id: | IJNRD2305248 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | The YOLOv8 algorithm is a deep learning-based object detection method that can recognize items inside an image with high accuracy. The system was trained on a huge collection of photos of employees wearing various PPE configurations, such as gloves, masks, goggles, and suits, allowing it to accurately recognize PPE usage. Real-time monitoring and alarms may be supplied to guarantee that safety standards are followed at all times by integrating the system with current security and safety monitoring systems. This technology integrates easily with current security and safety monitoring systems, enabling real-time monitoring and alarms to verify that safety standards are followed. The suggested method has the potential to considerably enhance chemical sector safety outcomes. The technology decreases the risk of accidents and injuries caused by PPE breaches by automating PPE detection. The system can also contribute to a safer working environment for employees by protecting them from dangerous chemicals and operations. Furthermore, by decreasing the requirement for manual monitoring and inspection by safety people, the system can increase operating efficiency and free up safety workers for other activities. Furthermore, by training the YOLOv8 algorithm on other datasets, this solution can be applied to multiple industries that need PPE compliance, such as healthcare and construction, allowing it to recognize particular forms of PPE, such as surgical masks and hard helmets. |
| Keywords: | PPE Detection, YOLO v8, Deep learning, chemical industries. |
| Cite Article: | "Personal Protective Equipment detection in chemical industry ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.c354-c359, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305248.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2305248 Registration ID: 194605 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: c354-c359 Country: Coimbatore, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305248 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305248 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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