AUTOMATED DETECTION OF PERSONAL PROTECTIVE EQUIPMENT (PPE) USING YOLOV8 FOR CONSTRUCTION SAFETY
Workplace safety in construction environments is a top priority to reduce the risk of accidents and ensure compliance with safety standards. Proper use of Personal Protective Equipment (PPE) is crucial in achieving this goal. CCTV is often employed to monitor PPE usage; however, human limitations...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/85005 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Workplace safety in construction environments is a top priority to reduce the risk of
accidents and ensure compliance with safety standards. Proper use of Personal
Protective Equipment (PPE) is crucial in achieving this goal. CCTV is often
employed to monitor PPE usage; however, human limitations in continuously
observing CCTV footage can lead to gaps in supervision. Therefore, an automated
system is needed to monitor CCTV recordings and detect PPE usage. This final
project aims to design a system, develop and implement a model, and evaluate the
system based on the conditions in the construction environment. The PPE detection
system will utilize the YOLOv8 model to recognize and detect PPE. The system's
development follows the CRISP-DM methodology, which includes the stages of
Business Understanding, Data Understanding, Data Preparation, Modeling,
Evaluation, and Deployment. The outcome of this project is a reliable PPE detection
system that can be operated in construction environments, thereby supporting the
implementation of workplace safety. After evaluating the system in a construction
environment, the developed PPE detection system achieved a precision of 0.848, a
recall of 0.560, and an F1-score of 0.676. |
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