Geospatial Semantics-Based Mapping of Digital Twin-Based Controls for Scalable Management of Targeted Fan-Assisted Cooling System

Digital twin (DT) technology offers promising advancements in building operations but faces scalability challenges due to the complexity of maintaining fixed control loops and semantic models. This study introduces a geospatial semantics-based DT framework for scalable and adaptive control loop management, demonstrated through its application to targeted fan-assisted cooling systems. By integrating geospatial data with logical reasoning, the framework automates control loop mapping for grid ceiling-embedded fans. Experimental validation with 120 participants in a shared office space tested three DT user interface designs (person-based, object-based, and suggestion-based controls) showing strong user satisfaction (p < 0.00) across all three interfaces. To ease the adoption our proposed approach, a plugin, geospatial semantics-BrickSchema integration, was developed to streamline geospatial data integration and semantic development through graphical programming. These findings highlight the framework’s potential to overcome scalability challenges in traditional building management systems, offering a flexible and sustainable solution for dynamic real-world environments.