Computer vision-based safety risk computing and visualization on construction sites

Abstract

Despite advancements in computer vision technology for construction site safety, the identification and evaluation of potential safety risks stemming from on-site hazardous objects and their spatial interactions is under-researched. Moreover, the subsequent visualization of risks, essential for effective safety management, remains insufficiently explored. This paper presents a model combining computer vision and the TOPSIS method to automate safety risk quantification and visualization during the construction process. Uniquely, it enhances risk predictions by dynamically monitoring the quantity and distance changes of hazard sources and their risk-related objects in real-time, beyond pre-construction risk identification and predictions. Experimental validation shows the model's effectiveness in risk quantification and visualization, with a high consistency ratio of 95% compared to expert manual assessments. This model lays the groundwork for more precise risk calculation and evaluation, fostering improved safety management decisions.