Digital Twin in Construction Safety and Its Implications for Automated Monitoring and Management

Abstract

With construction sites being dynamic and unstructured in nature, the safety of workers at a job site has always been a major concern for project managers, who often assign a significant portion of project resources and manpower for maintaining safety protocols. The current manual methods used for safety surveillance at a job site are not only laborious but also time-consuming and prone to human error, leading to numerous accidents at sites each year. This study proposes a new approach that employs a digital replica of a construction safety surveillance system capable of providing real-time safety analyses and predictions based on site conditions. A digital twin system developed in this study allows for real-time communication with a construction site facilitating safety managers in a decision-making process. The system encompasses three primary resources: (1) 4D BIM models, (2) cloud computing and database platforms, and (3) real-time field data captured by sensors and processed by artificial intelligence techniques. The proposed system is expected to improve real-time safety surveillance through identification of various site conditions and prediction of possible safety concerns.