Edinburgh Napier University

  Digital twins (DTs) are becoming integral in sectors such as energy and manufacturing, catalyzing applications from monitoring and analysis to optimization and autonomous management. However, data in different formats, volumes, and qualities require high processing capabilities for integration. Moreover, the functionalities in DTs must work together, bringing interoperability challenges that have necessitated extensive manual programming. To address these, we propose the Internet of Twins, a disaggregated DT deployed in a distributed cloud architecture where interconnections are made using a remote procedure call framework, gRPC. Using this, we develop DT as a platform with knowledge-graph-based orchestration. Here, we implement a recursive execution algorithm to ensure necessary data are processed in the correct sequence autonomously. Then, we implement a wind energy pilot application and evaluate the performance. The results show that our approach lowers data preprocessing and line-of-code overhead up to 20% and 26%, creating a flexible and scalable architecture.