
Generative AI and Generative AI of Things for Sustainable Smart Cities
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
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.
More details
Other editions
Additional editions


Person
Content
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
System requirements
File format: PDF
Copy-Protection: Adobe-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Install the free reader Adobe Digital Editions prior to download (see eBook Help).
- Tablet/smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook before downloading (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Adobe-DRM, a „hard” copy protection. If the necessary requirements are not met, unfortunately you will not be able to open the eBook. You will therefore need to prepare your reading hardware before downloading.
Please note: We strongly recommend that you authorise using your personal Adobe ID after installation of any reading software.
For more information, see our eBook Help page.