Digital Twin Technologies in Civil Infrastructure: A Comprehensive Literature Review Over the Recent Decades

Monitoring and predicting infrastructure system status are crucial aspects of urban planning and infrastructure management. Digital Twin (DT) technology got the attention of many researchers as it highlights the revolutionary step of early system prediction through real-time monitoring and improving the accuracy of making decisions. DT is a virtual representation reflecting real physical system behavior with bi-directional data interactions. This paper focuses on studying various applications of DT across various disciplines and simulation levels, emphasizing the impact of varying load types on the monitoring and prediction of structure health in real-time updating. The study investigates data collecting methods categorized into geometric and non-geometric methods, including the use of Internet of Things (IoT) devices, sensors, and Intelligent Transportation Systems (ITS). By presenting case studies and real-world applications of DT used on monitoring systems, this paper explains the improvements and successes reached with the implementation of the DT models in the infrastructure field. The findings highlight not only the ability of DT technology but also point out the gaps in the current research as a step for future researchers to enhance the efficiency of DT applications.