مهندسی عمران شریف (Feb 2021)
AUTOMATED ASSESSMENT OF FALL HAZARD RISK USING BUILDING INFORMATION MODELING AND IMAGE PROCESSING
Abstract
Statistics of Occupational Safety all around the world shows that construction industry in many countries such as Iran experiences one of highest accident rates among all industry sectors; therefore, safety has a prominent role in construction project progress which is related to injury and fatality rates of the project. Falls from height can be enumerated as a major concern because they contribute to a great part of fatalities in construction projects. Various studies have been conducted to assess the risk and enhance safety on the job site. Because of the inefficiency of traditional risk assessment methods (e.g., expert view gathering and documentation of past incidents), novel trends and technologies such as Building Information Modeling (BIM) were utilized to fulfill the gaps. Automation in the hazard recognition was also utilized in some previous studies to enhance the safety on the job site. This study presents a novel framework to identify and rank the hazardous areas regarding the fatal fall hazard risk drivers on construction projects through the execution phase. The developed framework employs a customized Application Programming Interface (API) to identify the probability of falling from the height in each opening area based on the BIM approach. It also makes use of an image processing analytical model to identify the softness of the surface underneath to estimate the impact of the risk factors that can be used in safety planning process. Thus, the developed framework assists the safety managers on the job sites to identify the fall risk factors automatically. The obtained results in a commercial case study indicate that this model is capable of anticipating the fall risk appropriately. Moreover, it was shown that edges of surfaces would be more prone to be dangers than internal ones and height of fall was the factor most affecting the results.
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