Smart Building Energy Management Using Digital Twins Technology

Abstract

Digital twin–based smart building energy management systems enable real-time monitoring, simulation, and optimization of building operations using data from sensors and IoT devices. By integrating advanced analytics and predictive control, these systems significantly reduce energy consumption, operational costs, and carbon emissions while maintaining occupant comfort. Although challenges related to interoperability, cybersecurity, and scalability remain, ongoing advances in AI, semantic modeling, and standardized architectures are improving practical adoption. Future developments will focus on renewable energy integration, occupant-centric control, and smart city–level energy optimization.