Digital twin-driven innovation in smart and green building: a structured review and research agenda

Abstract

Digital Twin (DT) technology is increasingly being adopted in the architecture, engineering, and construction sectors—particularly in smart and green buildings—to enhance sustainability, performance monitoring, and user comfort. This review analyses 93 peer-reviewed studies, systematically categorised into applications for smart buildings and green buildings. Key enabling technologies include Building Information Modeling (BIM), Internet of Things (IoT), and Artificial Intelligence (AI), all of which contribute to the integration, automation, and optimization capabilities of DTs. The findings highlight DT applications across energy management, predictive maintenance, occupant-centric control, and environmental monitoring. While several studies indicate that DTs have the potential to support objectives such as net-zero energy and waste, most evidence remains theoretical or based on simulations rather than empirically validated at the full building scale. Based on the review findings, the paper presents a research agenda comprising three core research gaps and five corresponding directions for future work. The study provides a comprehensive perspective on current trends while highlighting strategic pathways to advance DT adoption in sustainable built environments.