Multi-label material and human risk factors recognition model for construction site safety management.
Journal:
Journal of safety research
PMID:
39998535
Abstract
INTRODUCTION: Construction sites are prone to numerous safety risk factors, but safety managers have difficulty managing these risk factors for practical reasons. Moreover, manually identifying multiple risk factors visually is challenging. Therefore, this study aims to propose a deep learning model-based multi-label risk factor recognition (MRFR) framework that automatically recognizes multiple potential material and human risk factors at construction sites. The research answers the following questions: How can a deep learning model be developed and optimized to recognize and classify multiple material and human risk factors automatically and concurrently at construction sites, and how can the decision-making process of the model be understood and improved for practical application in preemptive safety management?