Integration of BIM and SHM For Sustainable Management of Existing Structures: A Systematic Review

Abstract

The integration of Building Information Modeling (BIM) with Structural Health Monitoring (SHM) represents a transformative approach for the sustainable management of existing structures. This review comprehensively examines the evolution, methodologies, applications, and future directions of BIM–SHM systems, emphasizing their potential to enhance structural safety, optimize maintenance, and support sustainability goals. Various integration techniques, including direct sensor-to-BIM linking, database-driven methods, and IoT-based real-time streaming, are critically analyzed, highlighting their advantages, limitations, and suitability for diverse infrastructure types. Application domains encompass bridges, high-rise buildings, heritage structures, industrial facilities, tunnels, and residential developments. The review further discusses the role of artificial intelligence and machine learning in predictive maintenance and automated BIM model updates, as well as the importance of embedding sustainability metrics into digital twins. Key challenges, such as lack of standardization, sensor data management, interoperability, scalability, and human skill gaps, are identified, providing insight into barriers to widespread adoption. Future research directions emphasize autonomous digital twins, robotics and UAV-assisted inspection, blockchain-based data security, and interdisciplinary collaboration. By synthesizing current knowledge and highlighting technological, operational, and sustainability considerations, this review provides a roadmap for researchers and practitioners aiming to advance BIM–SHM integration and realize resilient, efficient, and environmentally responsible infrastructure management.