Read more
This pioneering book invites readers on a compelling journey into Generative Artificial Intelligence (GAI) and its groundbreaking convergence with AI of Things (AIoT), introducing GAIoT as a transformative frontier in urban computing and intelligence. GAIoT signals a paradigm shift towards more intelligent, self-learning, self-evolving, and context-aware systems-capable of generating adaptive, forward-looking solutions to the complex infrastructural and environmental challenges confronting sustainable smart cities.
With its combination of theoretical depth, applied innovation, and interdisciplinary scope, the book offers a comprehensive examination of deep generative models-namely Generative Adversarial Networks, Variational Autoencoders, Diffusion Models, Transformers, and hybrid architectures-and their applications in environmental sustainability, climate resilience, infrastructure optimization, dynamic decision-making, and data-driven urban management and planning. From synthetic data generation, data augmentation, and data imputation to predictive modeling and scenario simulation, GAIoT is driving the next wave of climate-responsive, environmentally conscious smart city innovation.
What sets this book apart is its first-of-its-kind focus on GAIoT as a pathbreaking force in shaping the future of sustainable urban development. It delivers actionable insights, conceptual and operational frameworks, case studies, and policy guidance-equipping diverse stakeholders with the tools to build cities that not only respond to change but also anticipate and shape it. Targeting a broad and cross-disciplinary audience, the book shares state-of-the-art research, presents innovative solutions, and forecasts future trends in urban transformation. As both a seminal reference and a practical resource for researchers, technologists, practitioners, professionals, and policymakers, it provides essential guidance for those engaged in advancing the next frontier in urban computing and intelligence.
List of contents
Introduction: The Next Frontier in Urban Computing and Intelligence: Redefining Sustainable Smart Cities through Generative AI and Generative AI of Things
1. The Rise of Generative AI and Generative AI of Things for Sustainable Smart City Development: Innovations, Opportunities, Data Solutions, Applications, and Prospects
2. Deep Generative Models for Cognitive Augmentation of AI of Things in Sustainable Smart Cities: A Comparative Analysis of GANs, VAEs, Diffusion Models, Transformers, and Hybrid Models
3. Generative AI of Things for Sustainable Smart Cities: Recent Advancements in Environmental Efficiency, Infrastructural Optimization, and Climate Resilience
4. Generative AI at the Intersection of Smart Cities, Environmental Sustainability, and Climate Change: Conceptual, Analytical, Methodological, Technical, and Practical Foundations
5. Harnessing the Transformative Potential of Generative AI for Advancing Sustainable Smart City Development Goals: Leading-Edge Solutions for Environmental and Climate Challenges
6. Generative AI of Things-Powered Sustainable Smart City Brain and Digital Twin Systems: Synergizing Real-Time Operational Management and Strategic Predictive Planning
7. A Pioneering Generative AI of Things Framework for Sustainable Smart City Brain and Digital Twin Integration: Tackling Data Challenges to Advance Environmental Management and Planning
About the author
Simon Elias Bibri is a Senior Researcher, Project Coordinator, Editor-in-Chief, International Expert, and prolific scholar--with 8 authored books, 3 edited, and 11co-edited works, and an h-index of 53. Recognized by Stanford University and Elsevier, he has been ranked among the top 1% of scientists worldwide for five consecutive years.
