Multimedia knowledge-based bridge health monitoring using digital twin

Digital twins are virtual replicas of real physical entities in computers. They can be considered as abstract digital models of data and behavior for objects of interest. Nevertheless, they are not perfectly consistent with conventional data or simulation models because they achieve prediction and optimization by simulating the abstract digital model of a particular system. To maintain the characteristics of digital twins in the virtual space, digital simulation models that continue to update, change, and evolve according to continuous changes of corresponding physical factors must be used. Owing to the various advantages of digital twin technology, digital twins have gained more attention. However, the method to create digital twins is still unclear. Additionally, the availability and sufficiency of information on physical entities to which digital twins will be applied must be considered, and a model suitable for their application must be designed. Therefore, multimedia knowledge-based bridge health monitoring using digital twins is proposed herein. It synchronizes real and virtual spaces to reflect the reality based on various data collected using sensors of real systems. In this study, various situations of virtual bridge twins in a facility management area are simulated to provide digital services to ensure bridge health. This digital bridge health service analyzes situations based on a small amount of data collected from a bridge, predicts the optimal time point for maintenance, and then applies it to the real world. Hence, maintenance costs can be reduced and the bridge's lifespan extended.