A middleware for commissioning building digital twins

Digital twins (DT) are becoming essential for enhancing building operations via real-time monitoring, control, and predictive analytics. However, for optimal effectiveness, high-quality sensor data is crucial. Existing middleware solutions often encounter issues concerning openness, scalability, and automation in the context of building-specific workflows, which impede the seamless integration of heterogeneous data across different building control systems. Commensurate with this, we present a configurable middleware aimed at automating data aggregation, ensuring seamless device interoperability, and enabling bidirectional data flows for adaptive building control. The middleware is developed following architecturally significant requirements, which were systematically inferred from quality attributes and usage scenarios. A prototype implementation has been validated in a Living Lab environment to showcase the middleware’s ability to handle diverse, high-quality data while facilitating dynamic adaptations to real-time operational requirements. This study tackles significant shortcomings in current middleware solutions, offering a scalable and interoperable remframeworkmiddleware to enhance DT-enabled automation in building operations.