Advances, Applications, and Future Directions of Structural Health Monitoring in Civil Infrastructure: A Comprehensive Review

Abstract

Structural Health Monitoring (SHM) has emerged as a core discipline in modern civil engineering, providing a systematic means to safeguard the safety, durability, and long-term functionality of infrastructure. This review synthesizes current advancements in SHM for civil infrastructure, beginning with its foundational concepts and classification schemes, and progressing through key sensing technologies and their applications across the built environment. From bridges, tunnels, and high-rise buildings to culturally significant heritage structures, SHM has proven effective in detecting earlystage damage, optimizing maintenance schedules, and supporting rapid response following natural disasters or other disruptive events. Despite these capabilities, widespread adoption remains constrained by persistent challenges. These include sensor calibration drift over extended service periods, environmental and operational variability that obscures damage signals, the overwhelming volume of monitoring data requiring timely interpretation, and the absence of universal data and system standards. In response, the research community is advancing solutions such as real-time digital twins, machine learning–driven analytics, autonomous and self-powered sensing devices, and seamless integration with Building Information Modelling (BIM) platforms. Looking ahead, the continued evolution of SHM lies in enhancing interoperability, automating data interpretation, and ensuring the reliability of monitoring systems over the entire service life of assets. Achieving these objectives will position SHM as not merely a diagnostic tool, but as an essential component of predictive maintenance, smart asset management, and resilience planning within an increasingly complex and dynamic built environment. This review highlights three dominant trends across recent SHM research: the rapid shift toward data-driven diagnostics, the emergence of digital twin–integrated monitoring frameworks, and the increasing adoption of fibre-optic and wireless sensing technologies in large-scale deployments. Collectively, these trends point to a sector moving steadily toward autonomous, real-time, and lifecycle-oriented structural management.