The Generative AI-Driven Sustainable Smart City

Deep, Hybrid, and Foundation Models for Environmental Planning, Computational Design, and Climate Resilience
1. Auflage 2026
ISBN: 978-1-041-08723-6
Verlag: Taylor & Francis Ltd

Buch, Englisch, 352 Seiten, Format (B × H): 156 mm x 234 mm

The rapid rise of Generative AI is increasingly reshaping the field of urban computing, marking the next frontier of sustainable smart city research and practice. This book takes readers on an exploratory journey into the transformative potential of Deep Generative Models (DGMs), hybrid architectures, and Foundation Models (FMs) to redefine the future urban landscape. These technologies contribute to enhancing environmental sustainability, climate resilience, infrastructure performance, operational efficiency, spatial organization, and functional livability through forward-thinking approaches to urban planning, design, and management—often implemented via digital twins.

DGMs enable synthetic data generation, data augmentation, data imputation, scenario simulation, and predictive modeling, providing richer insights into complex urban systems. Hybrid architectures integrate generative and conventional models to improve robustness, scalability, and flexibility across diverse urban tasks. FMs extend these capabilities by facilitating knowledge generalization across datasets, supporting reasoning, and enabling adaptive decision-making under uncertainty. Strengthened by integrative frameworks and cross-disciplinary insights, these technologies offer powerful tools for developing sophisticated urban solutions. They advance how urban ecosystems are environmentally and strategically planned, efficiently and adaptively managed, aesthetically and functionally designed, and spatially and contextually organized.

Rich in conceptual frameworks, theoretical insights, operational models, applied innovations, practical case studies, and policy guidance, this book equips researchers, planners, designers, technologists, and policymakers to harness generative intelligence in shaping adaptive, context-aware, and continuously refined urban environments that are ecologically responsible, climate-resilient, and future-ready. Essential for anyone exploring the frontier of GenAI-driven urban development, it offers actionable insights to guide the next generation of sustainable smart cities.

Zielgruppe

Professional Practice & Development, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Huang, Jeffrey

Bibri, Simon Elias

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Geisteswissenschaften Architektur Städtebau, Stadtplanung (Architektur)
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1. The Rise of Deep Generative, Hybrid, and Foundation Models for Sustainable Smart City Intelligence: Theoretical Frameworks, Transformative Innovations, and Advanced Applications

2. Empowering Sustainable Smart City Digital Twins with Deep Generative and Foundation Models: A Pioneering Framework for Environmental Planning and Computational Design

3. Deep Generative and Hybrid Models for Advancing Environmental Sustainability in Smart Cities: Leading-Edge Solutions for Climate Change Mitigation and Adaptation

4. Deep Generative and Hybrid Models for Sustainable Smart Cities: Operational and Infrastructure Management, Strategic Planning, and Climate Resilience

5. Deep Generative and Foundation Models for Sustainable Smart City Digital Twins: Operational, Infrastructural, and Practical Advancements in Environmental Planning

6. Augmenting Computational Urban and Architectural Design with Deep Generative, Hybrid, and Multimodal Models in Smart Cities: Innovative Applications and a Cross-Scalar Disciplinary Framework

7. The Next Frontier in Sustainable Smart City Development: Urban, Flow, Environmental, Climate, and Geospatial Foundation Models for Multimodal Intelligence and Systemic Innovation

Über Autor(innen)

Simon Elias Bibri is a Senior Researcher, Project Coordinator, Editor-in-Chief, International Expert, and prolific scholar—with 9 authored, 3 edited and 12 co-edited books, and an h-index of 53. Recognized by Stanford University and Elsevier, he has been ranked among the top 1% of scientists worldwide for six consecutive years.

Jeffrey Huang is the Director of the Media and Design Lab and a Full Professor of Architecture and Computer Science. He graduated from ETH Zurich and Harvard University, taught at Harvard and Singapore University of Technology and Design, and co-founded Convergeo, an award-winning international strategic design firm.