Sensor-based crack detection in concrete structures, including technologies, challenges, and trends

Crack detection is key in Structural Health Monitoring (SHM) systems, which are important for the integrity, safety, and service life of critical infrastructure. As civil engineering structures such as bridges, tunnels, pavements, dams, and high-rise buildings age or are subjected to growing loads and impacts from the environment, the possibility of material degradation, particularly cracking, becomes a major concern. Early detection of cracks provides timely maintenance, minimizes repair costs, and prevents catastrophic failures. Recent developments in structural health monitoring (SHM) technologies have resulted in the creation of very sensitive, accurate, and non-intrusive systems for detecting early-stage degradation in reinforced concrete (RC) structures. This study offers a thorough overview of current developments in crack-detecting algorithms, focusing on state-of-the-art sensor technologies that have transformed traditional inspection methods. These technologies enhance the precision, automation, and scalability of SHM systems. This paper critically examines the advantages, limitations, and practical implementations of each technology, providing a comparative analysis that reflects current trends in research and industry adoption. This review concludes with a discussion on current challenges, such as sensor durability, data integration, false positives, and scalability, along with future directions, including wireless sensor networks, digital twins, autonomous UAV-based inspection, and edge AI for real-time decision-making. This work aims to provide engineers, researchers, and infrastructure managers with a clearer understanding of how modern sensor technologies are shaping the future of structural health monitoring and crack detection.