Construction safety monitoring is vital in enhancing site safety, such as tracking entering hazardous areas and the correlation between workers and other hazard entities. Therein, computer vision-based image/video processing, one of the emerging technologies, has been actively used to automatically identify and recognize unsafe conditions. However, the construction site has various potential hazard situations during the project. Due to the site’s complexity, many visual devices simultaneously participate in monitoring. It challenges developing and operating corresponding detection algorithms at specific workplaces and times. Besides, safety information detected by computer vision must be organized before being delivered to stakeholders. Hence, this study proposes an approach for construction safety monitoring using vision intelligence technology and BIM-cloud, called BMT. The BMT comprises two modules: (1) the virtual model based on the 4D BIM-cloud model, which provides the spatial-temporal information to decide computer vision algorithm adoptions
(2) the construction physical model built the vision intelligence technologies, which is supported by (1) and deliver safety status and update into the BIM-cloud model to visualize and deliver the risk level to related employees. The efficiency of the BMT approach is validated by testing with the preliminary implementation of a prototype.