List of Contributors xi -- Introduction xiii -- 1 Augmented Computational Design 1 -- Introduction 1 -- Background 2 -- Relevance of AI in AEC 2 -- Historical Context 3 -- Design as Decision-Making 5 -- AI for Generative Design 7 -- Framework 9 -- Design Space Exploration 11 -- Spatial Design Variables 13 -- Statistical Approaches to Design 14 -- Demonstration 15 -- Case Study 15 -- Methodology 16 -- Results 21 -- BBN Validation Results 21 -- Toy Problem 22 -- Discussion 22 -- Outlook 25 -- Acronyms 26 -- Notations 27 -- References 28 -- 2 Machine Learning in Urban Building Energy Modeling 31 -- Introduction 31 -- Urban Building Energy Modeling Methods 32 -- Top-Down Models 33 -- Bottom-Up Models 33 -- Uncertainty in Urban Building Energy Modeling 36 -- Epistemic Uncertainty 36 -- Stochastic Uncertainty 36 -- Addressing Uncertainty 37 -- Machine Learning in Urban Building Energy Modeling 39 -- Supervised Learning 39 -- Unsupervised Learning 44 -- Reinforcement Learning 46 -- Machine Learning-Based Surrogate UBEM 47 -- Conclusion 49 -- References 50 -- 3 A Hybrid Physics-Based Machine Learning Approach for Integrated Energy and Exposure Modeling 57 -- Introduction 57 -- Materials and Methods 59 -- Data, Data Sources, and Dataset Processing 59 -- Methodology 61 -- Results 70 -- Physics-Based Simulation 70 -- Data-Driven Computation (Prediction) 70 -- Discussion 73 -- Conclusion 74 -- Acknowledgment 75 -- References 75 -- 4 An Integrative Deep Performance Framework for Daylight Prediction in Early Design -- Ideation 81 -- Introduction 81 -- Background 83 -- Daylight Simulation 84 -- Deep Learning Models 85 -- DL-Based Surrogate Modeling 85 -- Verification Methods 85 -- Research Methods 86 -- Data Acquisition 86 -- Model Training 88 -- Results and Validation 88 -- Discussions of Results 90 -- Conclusions 94 -- References 94 -- 5 Artificial Intelligence in Building Enclosure Performance Optimization: Frameworks, Methods, and Tools 97 -- Building Envelope and Performance 97 -- Artificial Intelligence and Building Envelope Overview 97 -- Optimization Routes and Building Envelope 98 -- Optimization Frameworks 99 -- Optimization Methods 99 -- Machine Learning and Building Envelope 101 -- Artificial Neural Network 101 -- Convolutional Neural Network 105 -- Recurrent Neural Network 105 -- Generative Adversarial Networks 106 -- Ensemble Learning 107 -- Discussions on Practical Implications 108 -- Summary and Conclusion 109 -- References 110 -- 6 Efficient Parametric Design-Space Exploration with Reinforcement Learning-Based Recommenders 113 -- Introduction 113 -- Methodology 115 -- Section 01: Clustering Design Options 116 -- Section 02: Reinforcement Learning-Based Recommender System 120 -- Design Dashboard 123 -- Discussion 124 -- Conclusion 125 -- References 126 -- 7 Multi-Level Optimization of UHP-FRC Sandwich Panels for Building Façade Systems 129 -- Introduction 129 -- Building Façade Design Optimization 130 -- Methodology 134 -- Midspan Displacements and Thermal Resistivity of UHP-FRC Panels 136 -- Energy Performance of the UHP-FRC Panels at the Building Level 141 -- Life Cycle Cost Analysis of the UHP-FRC Panels 142 -- Surrogate Models 145 -- Multi-objective Optimization Algorithm 147 -- Results and Discussion 148 -- Surrogate Models 148 -- Pareto Front Solutions 151 -- Conclusion 152 -- References 153 -- 8 Decoding Global Indoor Health Perception on Social Media Through NLP and Transformer Deep Learning 159 -- Introduction 159 -- Literature Review 161 -- Social Media and Urban Life: Theories, Challenges, and Opportunities 161 -- Methods for Computing Social Media Data in Environmental Studies 163 -- Materials and Methods 168 -- Data Query 168 -- Text Preprocessing 169 -- Text Tokenization 169 -- Text Summarization 170 -- Generating Co-occurrence Matrix 170 -- Sentiment Analysis and Classification 170 -- Visualizations 171 -- Embedding Visualization 171 -- Attention Score Visualization (Attention Map) and Interpretation 172 -- Results and Discussion 173 -- Conclusion 178 -- References 179 -- 9 Occupant-Driven Urban Building Energy Efficiency via Ambient Intelligence 187 -- Introduction 187 -- Occupancy and Building Energy Use 191 -- Definitions 191 -- Occupant Monitoring Methods 193 -- Occupant Monitoring Via Observational Studies 194 -- Occupant Monitoring via Experimental Studies 195 -- Occupant-driven Energy Efficiency via Ambient Intelligence 196 -- Ambient Intelligence Advancements and Applications 196 -- AmI-Based Energy Efficiency Feedback (EEF) Systems 197 -- Energy Efficiency via AmI Systems and Digital Twins Technology 201 -- Conclusion 202 -- References 203 -- 10 Understanding Social Dynamics in Urban Building and Transportation Energy Behavior 211 -- Introduction 211 -- Methodology 213 -- Modeling Framework 214 -- Explanatory Model 214 -- Data 215 -- Results and Discussion 219 -- Effects of Occupancy and Socio-economic Factors 219 -- Variable Importance (VI) 219 -- Lek's Profile 219 -- Conclusion 226 -- References 227 -- 11 Building Better Spaces: Using Virtual Reality to Improve Building Performance 231 -- Introduction 231 -- Applications of Virtual Reality in Building Performance 233 -- Virtual Reality for Improving Building Design through Integrated Performance Data 233 -- Virtual Reality for Building Design Reviews and Education in Architecture and Engineering 236 -- Virtual Reality for Research on Building Occupant Comfort and Well-Being 240 -- Conclusion 243 -- References 245 -- 12 Digital Twin for Citywide Energy Modeling and Management 251 -- Introduction 251 -- Urban Building Energy Digital Twins (UBEDTs) 252 -- Definition and Conceptualization 252 -- Implications for Citywide Energy Management 254 -- Enabling Technologies 256 -- Twining Technologies 256 -- Urban Digital Twin(UDT) and Data Sources 258 -- Artificial Intelligence (AI) and Digital Twin 260 -- Relationship Between IoT, Big Data, AI-ML, and Digital Twins 261 -- Interoperability Technologies 262 -- Maturity Levels 263 -- Architecture 265 -- Data Acquisition Layer 266 -- Transmission Layer 266 -- Modeling and Simulation Layer 266 -- Data/Model Integration Layer 269 -- Service/Actuation Layer 269 -- Challenges in Implementing Citywide Digital Twins 269 -- Data Quality and Availability 270 -- Required Smart Infrastructure and Associated Cost 270 -- Interoperability 270 -- Data Analysis 271 -- Cybersecurity and Privacy Concerns 271 -- Conclusion 272 -- References 272 -- Index 277.