Computer Vision and AI in Structural Health Monitoring and Structural Engineering

In an era of aging infrastructure and an increasing demand for safety, structural health monitoring (SHM) has become critical for ensuring the longevity and reliability of buildings, bridges, and other essential structures. Computer Vision and AI in Structural Health Monitoring and Structural Engineering explores cutting-edge approaches to SHM, integrating advancements in computer vision, artificial intelligence (AI), and multimodal technologies to revolutionize how infrastructure is monitored, maintained, and managed. Starting with the fundamentals of SHM and structural engineering, the book examines the transformative power of computer vision applications, such as crack detection, corrosion assessment, and real-time deformation analysis. It also introduces vision-language models (VLMs), enabling automated defect reporting, multimodal analysis, and natural language interfaces for SHM systems.

• Provides in-depth coverage of how computer vision and AI technologies transform structural health monitoring (SHM)
• Focuses on the emerging vision-language models, which enable automated defect description, multimodal damage assessment, and natural language interfaces for SHM systems, making monitoring processes more intuitive and efficient for users
• Features case studies on bridge monitoring systems, building inspections, and infrastructure maintenance projects, showcasing successful implementations of advanced SHM techniques
• Explores cutting-edge technologies like 5G, edge computing, advanced sensors, and extended reality, highlighting their potential role in the future of SHM and offering readers a forward-looking perspective on the field