The Role of SHM in Retrofitting and Life-Cycle Management of Aging Buildings: A Comprehensive Review

Abstract

Aging building stock and the increasing complexity of urban infrastructures have highlighted the urgent need for effective strategies to assess, maintain, and retrofit civil structures. Traditional inspection methods, including visual assessment and destructive testing, are often insufficient for capturing the subtle and progressive deterioration inherent in aging infrastructure. Structural Health Monitoring (SHM) has emerged as a transformative approach, enabling continuous, real-time assessment of structural integrity through advanced sensing technologies, data-driven analytics, and integration with digital tools. This comprehensive review examines the role of SHM in the retrofitting and lifecycle management of buildings, focusing on technological advancements, methodological frameworks, and practical applications across diverse structural typologies, including bridges, high-rise buildings, and heritage masonry structures. The review critically evaluates sensor systems, including fiber-optic, wireless, and smart sensor networks, as well as data analytics techniques incorporating artificial intelligence and machine learning for automated damage detection and predictive maintenance. Furthermore, the integration of SHM with Building Information Modeling (BIM) and Digital Twin platforms is discussed as a key enabler for lifecycle optimization and retrofit decision support. Challenges in sensor deployment, data management, environmental robustness, and standardization are highlighted, alongside emerging trends and research gaps. The findings underscore SHM’s potential to enhance safety, extend service life, reduce economic risks, and support sustainable infrastructure management, providing a roadmap for future research and practical implementation in civil engineering.