Geotechnics and Generative Artificial Intelligence

This contributed volume examines how geotechnical engineering is being reshaped by the convergence of sustainable construction practices and generative artificial intelligence. It focuses on soil and rock systems as dynamic materials that can be analyzed, designed, and managed through data-driven methods and environmentally responsible engineering principles. The chapters in this volume examine how AI and green technologies together can reduce environmental impact while improving the precision and efficiency of geotechnical work.

The discussion spans advances in soil mechanics, predictive modelling, and sustainable ground engineering. Attention is given to AI-based soil classification, estimation of geotechnical parameters, and computational approaches to slope stability and foundation design. The book also explores bio-mediated soil improvement, reuse of construction waste in geotechnical applications, and strategies for lowering carbon intensity in infrastructure development. The book examines how machine learning, deep learning, and large language models support predictive analysis, design optimization, and decision-making in complex ground conditions. It also considers digital twins, autonomous site investigation systems, and AI-supported risk assessment tools that are beginning to reshape how projects are planned and delivered.

Rather than treating technology and sustainability as separate concerns, the book shows how they increasingly operate together to redefine engineering practice.