Enhancing Construction Site Safety: A Deep Learning Approach for Detection and Monitoring of Safety Equipment

This study uses magical YOLOv8 convolutional neural network model to improve the safety level in construction sites by identifying safety gears based on two dataset of PPE Object Detection Dataset V9 Pictor V3-revised and such dataset designed inside Bangladesh construction industry. The YOLOv8 model also proves to be versatile and dependable having reached a mean Average Precision (mAP) on wearable in PPE bmi 80.1% and 79.72% on the custom set. All the above are aimed towards emphasizing its usefulness for proper implementation which will help to minimize risks positively and safer working environment for the employees. This research is a huge milestone in the revolutionizing of safety monitoring systems within the construction environments.