Preface
List of Abbreviations
AI and Building Industry Impacts in Perspective
Environmental Costs of Construction
Challenges in Sustainable Constructions
AI and the Environment: Tools and Trade-offs
Potential for AI in Normalizing Sustainable Building Structures
Measuring the Sustainability of Building Structures
How to Measure the Carbon Footprint
The Building Structure and Its Carbon Footprint
Bringing Back Material-Efficient Structural Designs
Bio-Based Materials as Carbon Sinks and Other Alternative Materials
Building Renovations and When Not to Build
Recycling, Reusing and Rethinking Traditional Building Materials
The Technological Challenge for a Holistic Approach to Sustainable Design
The Digital Transformation in Construction
Balancing Sketches, CAD and Algorithms in Building Design
Project Documentation with BIM
Advances in Materials Science and Automation in Construction Sites
Project Communication in the Post-Pandemic Era
Machine Learning and Big Data
Introduction to Machine Learning
A Discussion with Alexander Stirken on Software Development in the Building Industry and the Challenges and Potentials of Machine Learning
Data Driven Carbon Footprint Estimation
Surrogate Models for Fast Estimations and Energy Savings in Simulation
Application to Structural Health Monitoring to Extend the Life-Cycle of Structures
Improving Point Cloud Workflows for Building Scans
Discovering New Construction Materials
A Bridge to Visual Programming for More Flexible Machine Learning Workflows in Building Design
Large Language Models
How Large Language Models Think
Conversation with Alexander Forsch About Leveraging Applied Research and Large Language Models to Enhance Project Sustainability and Strategies for Managing Data Centers Within Sustainable Urban Planning
AI Bots for Sustainable Building Design
Embeddings and Semantic Searches in Life-Cycle Assessments
Expanding Sustainability Bots’ Knowledge Through Retrieval-Augmented Generation and Fine-Tuning
Code Vibing Data Exchange for Life-Cycle Assessment Dashboards
Multimodal Generative AI
Text-to-Image: Enhancing Sustainable Building Storytelling with Diffusion Models
Image-to-image and 3D-to-image: Towards Honest Architectural Visualizations
Interview with Cas Esbach on how state-of-the-art AI Visualizations can Catalyze Sustainable Building Projects
Image-to-Text: Bridging the Gap Between the Built Environment and Large Language Models
Other Multimodal Workflows
AI Agents
Introduction to AI Agents and Model Context Protocol
Deep (Re)search Agents for Innovative Sustainable Planning
Automating Project Management with AI Agents and Other Productivity Hacks
Enabling AI Assistants in Building Design
Towards Online AI Agents to Reduce the Carbon Footprint of Basic Buildings
Reinforcement Learning
Reinforcement Learning Agents
Enabling Circular Economy in Building Design
AI-Powered Robotics in Construction
Enhancing Large Language Models with Reinforcement Learning
Conclusions
Insights Gained Along the Journey
Ensuring Safe Implementation of AI in the Building Industry
A Positive Outlook
References
Index
Biography
Dr. Diego Apellániz is a structural engineer with more than ten years of professional experience and a solid foundation in programming and AI. His doctoral research explored how parametric design and machine learning can support early design decisions that lead to more sustainable buildings. He received the European 2024 EFCA Future Leader award, recognizing his leadership and his role as an AI enabler in the engineering sector.
