Digital Twin Technology for Structural Lifecycle Management and Health Monitoring

Digital twin (DT) technology is reshaping structural engineering by linking physical assets to dynamic and data-driven virtual counterparts. DTs enable monitoring, predictive analytics, and autonomous decisions across design, construction, operation, and maintenance. Additionally, DTs are updated with real-time streams continuously. This study focuses on the applications of DTs and the intersection between the Internet of Things (IoT), Building Information Modeling (BIM), and artificial intelligence (AI). Applications include structural health monitoring (SHM) and predictive maintenance for bridges and buildings, in addition to construction safety optimization and stewardship of architectural heritage. The paper also examines barriers to adoption, including data interoperability, cybersecurity, upfront cost, and workforce readiness, and discusses standardization needs. In addition, it highlights educational impacts and pathways for small and medium enterprises (SMEs) to adopt scalable DT solutions. By consolidating recent advances, the review shows how DTs can deliver more resilient, efficient, sustainable, and intelligent infrastructure and outlines the research priorities to overcome remaining gaps and fully realize their potential.