Book

Advanced Deformation Monitoring for Engineering Infrastructure Technologies, Data Analytics, Artificial Intelligence, and Digital Twins The safety, resilience, and long-term performance of engineering infrastructure depend increasingly on the ability to detect, understand, and predict deformation. Advanced Deformation Monitoring for Engineering Infrastructure provides a comprehensive overview of how modern sensing technologies, data analytics, artificial intelligence, and digital technologies are transforming infrastructure monitoring. The book examines conventional geodetic techniques alongside advanced remote-sensing methods, including GNSS, total stations, InSAR, terrestrial laser scanning, LiDAR, and UAV photogrammetry. It also addresses the computational workflows required to convert raw observations into reliable deformation information, including time-series analysis, point-cloud processing, change detection, and multi-sensor data fusion. Particular attention is given to artificial intelligence and machine learning for anomaly detection, deformation prediction, structural assessment, and early-warning applications. The emerging roles of explainable AI, IoT, cloud and edge computing, and digital twins are explored as foundations for intelligent and increasingly autonomous monitoring systems. Practical applications and recent case studies cover dams and hydraulic structures, bridges, tunnels, slopes and landslides, mining areas, and urban infrastructure affected by land subsidence. The book also considers standards, monitoring protocols, economic factors, technical challenges, uncertainty, and future research directions. Integrating geodesy, civil and structural engineering, geotechnical engineering, remote sensing, data science, and artificial intelligence, this book is a valuable reference for researchers, engineers, academics, postgraduate students, infrastructure managers, and professionals working in structural health monitoring, geohazard assessment,and resilient infrastructure management.