Application of digital twin technology for monitoring residential buildings

Abstract

The rapid digitalization of the construction industry has led to the development of advanced technologies for monitoring and managing the condition of buildings and infrastructure. One of the most promising approaches is Digital Twin technology, which creates a dynamic digital representation of a physical object by integrating digital models with real-time monitoring data. This study investigates the application of Digital Twin technology for monitoring residential buildings in Uzbekistan, a region characterized by high seismic activity. The proposed framework integrates Building Information Modeling (BIM), sensor-based Structural Health Monitoring (SHM), and cloud-based data analytics to provide continuous assessment of structural performance. The methodology includes the development of a detailed BIM model of the building, the installation of a network of structural and environmental sensors, and the integration of collected data into a digital twin platform for real-time analysis and visualization. The system enables monitoring of vibration characteristics, deformation, and environmental effects on structural elements. The results demonstrate that the integration of digital models, sensor networks, and artificial intelligence technologies allows early detection of structural anomalies, supports predictive maintenance strategies, and improves the reliability and safety of residential buildings. The proposed approach can serve as a technological basis for developing digital seismic passports of buildings and implementing smart infrastructure monitoring systems in Uzbekistan and other seismically active regions