Digital Twin-based construction quality and safety model of urban elevated bridge

The intricate nature, unpredictability, and risks linked to contemporary urban elevated bridge projects pose challenges to conventional construction quality and safety management methods. Information technology plays a crucial role in supporting and ensuring the construction and management of urban infrastructure projects. This research presents a case study and introduces a construction quality and safety early warning model and system framework utilizing digital twin (DT) technology for the control of quality and safety through “identification, warning, and control.” The suggested approach integrates Building Information Modeling (BIM), Internet of Things (IoT) sensors, big data analytics, and other technologies, featuring modules for quality and safety data collection and analysis, continuous automated monitoring, early warning of potential issues, and visual decision-making. The findings indicate that the DT-based early warning model and system enhance inspection, monitoring, analysis, and decision-making for early warnings in elevated bridge projects, significantly facilitate the management of urban elevated bridge construction.