AI in Structural Engineering

The built environment is facing new challenges-rising urban populations, aging infrastructure, and the increasing frequency of extreme weather events are pushing structural systems to their limits. At the same time, advances in data collection technologies, such as smart sensors and IoT devices, are generating vast amounts of structural performance data. AI in Structural Engineering: Leveraging Structural Data for Safer Buildings explores how artificial intelligence can bridge the gap between raw structural data and actionable insights, transforming the way engineers design, monitor, and maintain safer buildings.


This book is intended for structural engineers, data scientists, researchers, and students interested in the convergence of engineering and AI. It provides a comprehensive look at how machine learning, deep learning, and predictive analytics can be applied to stress analysis, load forecasting, health monitoring, and failure prevention. With a balance of theory, real-world case studies, and practical methodologies, this book aims to equip readers with the knowledge and tools needed to harness AI for making buildings not only smarter-but fundamentally safer.