Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli

The manufacturing and construction sectors have consistently experienced a high incidence of occupational accidents and diseases. In response, many countries, including Malaysia, have incorporated the use of Personal Protective Equipment (PPE) into their government laws and safety regulations. In Ma...

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Main Author:	Mohamad Nazli, Nur Amielia Natasha
Format:	Thesis
Language:	English
Published:	2023
Subjects:	Information technology Information systems
Online Access:	https://ir.uitm.edu.my/id/eprint/89020/1/89020.pdf
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id	my-uitm-ir.89020
record_format	uketd_dc
spelling	my-uitm-ir.890202024-03-19T07:08:13Z Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli 2023 Mohamad Nazli, Nur Amielia Natasha Information technology. Information systems The manufacturing and construction sectors have consistently experienced a high incidence of occupational accidents and diseases. In response, many countries, including Malaysia, have incorporated the use of Personal Protective Equipment (PPE) into their government laws and safety regulations. In Malaysia, this requirement is outlined in Standard Operation Procedure (SOP) manuals, which specify the mandatory use of seven types of PPE: hard hat, safety goggle, hi-vis vest, safety shoes, gloves, respirator, and earplugs. However, monitoring a large number of workers and ensuring consistent use of PPE can be challenging when done by human agents. Therefore, the objectives of this project involve design and implementation of a real-time PPE detection system, which aims to effectively monitor workers’ safety compliance. The project utilizes the You Only Look Once (YOLO) algorithm as the detection algorithm, namely version 5. Images were collected to train the model on detecting workers wearing PPE or not. In this project, the methodology used is the modified waterfall model, which consists of four main phases excluding the maintenance phase, covering requirement analysis, design, implementation and testing. For this project, there are two types of testing were conducted: functionality testing of the performance of the entire system and metric evaluation to evaluate the accuracy of the object detection model. The object detection algorithm achieved a mean Average Precision (mAP) of 91.5% in the metric evaluation, while the accuracy testing yielded a 98.3% accuracy rate. In order for the system to easily access by the targeted users, companies in the manufacturing and construction sectors and the Occupational Safety and Health Act (OSHA), the system was developed as a web-based platform. As a recommendation for future work, enhancing the detection model for other types of PPE and make the system more reliable for every sector. 2023 Thesis https://ir.uitm.edu.my/id/eprint/89020/ https://ir.uitm.edu.my/id/eprint/89020/1/89020.pdf text en public degree Universiti Teknologi MARA, Melaka College of Computing, Informatics and Mathematics
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Information technology Information systems
spellingShingle	Information technology Information systems Mohamad Nazli, Nur Amielia Natasha Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli
description	The manufacturing and construction sectors have consistently experienced a high incidence of occupational accidents and diseases. In response, many countries, including Malaysia, have incorporated the use of Personal Protective Equipment (PPE) into their government laws and safety regulations. In Malaysia, this requirement is outlined in Standard Operation Procedure (SOP) manuals, which specify the mandatory use of seven types of PPE: hard hat, safety goggle, hi-vis vest, safety shoes, gloves, respirator, and earplugs. However, monitoring a large number of workers and ensuring consistent use of PPE can be challenging when done by human agents. Therefore, the objectives of this project involve design and implementation of a real-time PPE detection system, which aims to effectively monitor workers’ safety compliance. The project utilizes the You Only Look Once (YOLO) algorithm as the detection algorithm, namely version 5. Images were collected to train the model on detecting workers wearing PPE or not. In this project, the methodology used is the modified waterfall model, which consists of four main phases excluding the maintenance phase, covering requirement analysis, design, implementation and testing. For this project, there are two types of testing were conducted: functionality testing of the performance of the entire system and metric evaluation to evaluate the accuracy of the object detection model. The object detection algorithm achieved a mean Average Precision (mAP) of 91.5% in the metric evaluation, while the accuracy testing yielded a 98.3% accuracy rate. In order for the system to easily access by the targeted users, companies in the manufacturing and construction sectors and the Occupational Safety and Health Act (OSHA), the system was developed as a web-based platform. As a recommendation for future work, enhancing the detection model for other types of PPE and make the system more reliable for every sector.
format	Thesis
qualification_level	Bachelor degree
author	Mohamad Nazli, Nur Amielia Natasha
author_facet	Mohamad Nazli, Nur Amielia Natasha
author_sort	Mohamad Nazli, Nur Amielia Natasha
title	Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli
title_short	Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli
title_full	Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli
title_fullStr	Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli
title_full_unstemmed	Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli
title_sort	real-time personal protective equipment (ppe) compliance detection system using you only look once version 5 / nur amielia natasha mohamad nazli
granting_institution	Universiti Teknologi MARA, Melaka
granting_department	College of Computing, Informatics and Mathematics
publishDate	2023
url	https://ir.uitm.edu.my/id/eprint/89020/1/89020.pdf
_version_	1794192189252698112

Real-time Personal Protective Equipment (PPE) compliance detection system using you only look once version 5 / Nur Amielia Natasha Mohamad Nazli

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