AI-Driven Solutions for Greening the Built Environment. Integrating Circular Economy, Smart Technologies, and Resilience. Woodhead Publishing Series in Civil and Structural Engineering

AI-Driven Solutions for Greening the Built Environment: Integrating Circular Economy, Smart Technologies, and Resilience provides an authoritative resource on the integration of artificial intelligence (AI) within sustainable building practices, targeting the greening of the built environment by combining circular economy principles, smart technologies, and resilience strategies. It addresses the urgent need for improved energy efficiency, adaptive management, and reduced environmental impact across the building lifecycle, at a time when the sector faces mounting pressures from climate change, rapid urbanization, and resource scarcity. The book explores how AI-driven tools-such as generative design, digital twins, blockchain, and advanced sensing-enable dynamic decision-making, optimize material flows, and enhance occupant comfort, safety, and building adaptability. Organized in three parts, it covers AI in the circular economy, smart technologies, and building resilience, each presenting practical approaches, modeling techniques, and case studies. The structure ensures comprehensive coverage for academic researchers and practitioners, while bridging theory with actionable strategies. Timely and significant, this volume will be an essential reference for professionals, policy makers, and academics seeking cutting-edge, future-proof solutions for sustainable construction.

1. Introduction

Part 1: Leveraging AI for a Circular Economy
2. The Role of AI in Improving Materials’ Circularity Performance
3. Towards AI futures for the circular adaptive reuse of buildings
4. Using AI to Predict CO2 Emissions at the Building Demolition Stage
5. Housing Passport to enhance circular economy in residential buildings

Part 2: AI-Enabled Smart Technologies
6. Generative Design in the Built Environment
7. AI-driven Design Optimization for Sustainable Buildings
8. Unleashing the Potential of Artificial Intelligence in Construction
9. Novel BIM-Derived Dataset for AI-Driven Energy Consumption Prediction
10. (AI) and (BIM) Technologies for Sustainable Building in the Context of Smart Cities
11. AI-Integration of Digital Twins and Blockchain for Smart Building Management
12. AI-Optimization of Building Energy Efficiency and Occupants' Comfort

Part 3: Harnessing AI Solutions to Strengthen Building Resilience
13. Utilizing AI-Techniques for Efficient Condition Assessment of Building Components
14. AI-Solutions to tackle Fa�ade Fires in High-Rise Buildings
15. AI for Detecting Building Defects
16. AI in Optimization of the Stability of the Walls Against Wind Loads in Building Design
17. Integrating Circular Economy and Life Cycle Assessment Strategies in Climate-Resilient Buildings
18. Integrating AI, and sensor technology for engineering disasters mitigation in steel buildings
19. Technologies for Disaster Prevention Based on Intelligent Monitoring of Building Structures

Authors

Fernando Pacheco-Torgal Principal Investigator, CTAC Research Centre, University of Minho, Guimaraes, Portugal. Fernando Pacheco Torgal is a Principal Investigator at C-TAC, University of Minho. He holds the title of Counsellor (Top 0.5%) from the Portuguese Engineers Association and has been consistently recognized as a Scopus Highly Cited Scientist in the global rankings by Stanford University. With over 300 publications to his name, he has carried out in-depth peer reviews of more than one thousand scientific papers and assessed nearly one hundred research grant proposals across 15 countries. He serves on the editorial boards of nine international journals and has been involved in editorial decisions for several hundred manuscripts. In addition, he has edited 33 international books, many of which are available in the libraries of prestigious institutions such as Harvard, MIT, and Stanford. Zhao Xin-Yu State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, P.R. China. Zhao Xin-Yu, is a full Professor at the South China University of Technology, and is an expert in recycled aggregates.

Table of Contents

Authors

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