Smart Industrial Safety using Computer Vision

Bhana, Rehan and Mahmoud, Haitham and Idrissi, Moad (2023) Smart Industrial Safety using Computer Vision. In: 2023 28th International Conference on Automation and Computing (ICAC), 30th August - 1st September 2023, Birmingham, United Kingdom.

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Abstract

More than 2.3 million people worldwide suffer from work-related injuries or illnesses each year, resulting in more than 6,000 deaths per day. Providing an unclear work environment and failing to wear appropriate personal protective equipment have been identified as significant contributors to workplace accidents, making it imperative that employers prioritize workplace safety as a priority. Providing proper personal protective equipment (PPE) and maintaining a well-organized, clearly marked (unsafe) work environment can help prevent inconvenient workplace incidents. Furthermore, it promotes a safe working environment, reduces the likelihood of life-threatening events, and enhances overall business and economic conditions. Therefore, this paper proposes safe, smart manufacturing by implementing computer vision technology to detect appropriate PPE worn by workers and ensure a safe workspace to reduce the risk of human injuries. By utilising computer vision technology, we can identify PPE, such as gloves, helmets, and working forklifts, used by workers in the manufacturing environment. A precision of 80.6% and 86% have been reached using YOLOv8 for all classes in both datasets. In general, an extensive review of both datasets, including five performance metrics, is considered.

Item Type:	Conference or Workshop Item (Paper)
Identification Number:	10.1109/ICAC57885.2023.10275164
Dates:	Date Event 1 August 2023 Accepted 16 October 2023 Published Online
Uncontrolled Keywords:	Smart Manufacturing, Industrial warehouse, Computer vision, Manufacturing 4.0, Machine learning
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Gemma Tonks
Date Deposited:	12 Mar 2024 11:29
Last Modified:	12 Mar 2024 11:29
URI:	https://www.open-access.bcu.ac.uk/id/eprint/15336

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