Saving Energy with Comfort: A Semantic Digital Twin Approach for Smart Buildings

Building Energy Management Systems (BEMS) aim to optimize building assets for saving energy without compromising humans’ comfort. BEMS must integrate heterogeneous components and complex architectures for monitoring building conditions and controlling building assets such as lights, heating, and air ventilation systems. To tackle interoperability issues and support heterogeneity in smart environments (smart buildings), semantic technologies have been extensively used. Semantically interlinked/integrated information related to energy optimization and comfort in smart buildings can be effectively utilized in decision support tools/systems, if it is efficiently provided to decision makers, via their digital twins. Visualizing semantically integrated real-time sensor information within the digital asset, and supporting the real-time actuation of semantically annotated assets via the interaction with their digital twin, can support decision making in smart buildings for saving energy with comfort. In this paper, a semantic digital twin approach for smart buildings is proposed, along with a first prototype implementation in the energy-saving domain.