<![CDATA[Digital Twin technology has emerged as a promising approach for improving structural health monitoring (SHM) in smart buildings through real-time data integration, virtual modeling, and predictive analysis. However, a comprehensive theoretical framework integrating Digital Twin concepts within SHM systems remains limited in civil engineering research. This study aims to develop a theoretical Digital Twin framework for structural health monitoring in smart buildings using a literature review approach. The review examines previous studies related to Digital Twin, Building Information Modeling (BIM), Internet of Things (IoT), sensor technologies, and artificial intelligence in smart infrastructure applications. The findings identify key components and integration mechanisms required to support real-time monitoring, anomaly detection, and predictive maintenance of building structures. The proposed framework contributes to the development of intelligent, resilient, and sustainable smart building systems and provides a conceptual foundation for future research and practical implementation in civil engineering.]]>
Copyrights © 2026
