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Elsevier

The Next Frontiers of Quantum Generative Intelligence for Smarter Eco-Cities

Transforming Environmental Sustainability Through Augmented Deep Generative and Foundation Models

  • 1st Edition - August 1, 2026
  • Latest edition
  • Author: Simon Elias Bibri
  • Language: English

The Next Frontiers of Quantum Generative Intelligence for Smarter Eco-Cities: Transforming Environmental Sustainability Through Augmented Deep Generative and Foundation Mo… Read more

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Description

The Next Frontiers of Quantum Generative Intelligence for Smarter Eco-Cities: Transforming Environmental Sustainability Through Augmented Deep Generative and Foundation Models presents groundbreaking advances in the convergence of quantum computing, artificial intelligence, deep generative models, foundation models, and urban and environmental systems to transform sustainable urban development practices. The book offers conceptual frameworks, theoretical insights, evidence syntheses, applied innovations, operational models, empirical case studies, and real-world use cases that showcase how various forms of quantum-enhanced intelligence can advance the analysis, simulation, prediction, and optimization of energy systems, transportation networks, mobility flows, water and waste systems, biodiversity and ecosystems, air quality dynamics, and carbon capture processes while strengthening climate resilience in smarter eco-cities.

Detailed chapters examine deep generative models, hybrid and mixed architectures, urban and environmental foundation models, hybrid quantum-classical architectures, quantum generative adversarial networks, quantum variational autoencoders, quantum diffusion models, and quantum transformer-based models, providing readers with foundational knowledge, applied methodologies, and practical solutions. The book bridges theoretical advances with deployment strategies, encompassing policy guidance and system constraints to support evidence-based decision-making in urban ecological sustainability contexts.

This seminal resource benefits urban planners, city managers, environmental scientists, policymakers, technology experts, academics, and graduate students by equipping them with innovative tools and frameworks to design, operate, manage, and plan smarter eco-cities. It serves researchers and practitioners at the intersection of quantum AI, quantum generative AI, and urban-environmental systems, fostering interdisciplinary collaboration to address the urgent challenges of ecological degradation, resource depletion, and climate change.

Key features

  • Presents quantum-enhanced generative modeling frameworks that improve scalability, uncertainty quantification, and predictive accuracy for complex urban-environmental systems
  • Demonstrates applied case studies across multiple domains such as energy, transportation, biodiversity, and climate resilience, offering practical insights and measurable impacts for implementing cutting-edge technologies
  • Provides integrated operational and strategic frameworks that translate advanced computational intelligence into scalable, adaptive urban decision-making and policy guidance, empowering stakeholders to optimize sustainable urban infrastructure

Readership

Urban planners and city developers; environmental scientists and researchers; policymakers and government officials; technology experts and data scientists; city managers and administrators; academics and researchers in sustainability, urban planning, and computational intelligence, graduate students and advanced learners in AI, QC, and sustainable urban systems

Table of contents

  1. The Rise of Quantum Generative Artificial Intelligence in Smarter Eco-Cities: Evolutionary Dynamics, Computational Advancements, Emerging Applications, and Implementation Challenges
  2. Deep Generative, Hybrid, and Mixed Architectures for Smarter Eco-City Intelligence: A Synthesis of Conceptual, Architectural, Functional, and Practical Dimensions
  3. Pretrained, Adapted, and Multimodal Foundation Models for Smarter Eco-Cities: A Geospatial, Language, Vision, and Timeseries Approach to Urban-Environmental Intelligence
  4. Integrating Quantum Computing with AI and Generative AI: Theoretical, Technical, Computational, Synergistic, and Practical Foundations and Implications for Smarter Eco-Cities
  5. The Next Frontier of Deep Generative, Hybrid, and Mixed Modeling for Smarter Eco-City Intelligence: Leading-Edge Solutions for Advancing Environmental Sustainability Goals
  6. A Multilayered Framework for Deep Generative, Hybrid, and Mixed Modeling Toward Smarter Eco-City Intelligence: Cross-Domain Convergence, Implications, Challenges, and Research Directions
  7. The Next Wave of Generative Smarter Eco-City Modeling: Unifying Urban and Environmental Foundation Models for Adaptive, Scalable, and Multimodal Intelligence
  8. Quantum GANs and VAEs for Smarter Eco-Cities: Integrating Architectural Paradigms, Empirical Performance, and Practical Feasibility for Urban-Environmental Intelligence
  9. Quantum Diffusion Models for Smarter Eco-Cities: Generative, Synergistic, and Algorithmic Advances and Pathways for Urban-Environmental Intelligence
  10. Quantum Transformers and Language and Vision Foundation Models for Smarter Eco-Cities: A Hybrid Framework for Augmented Generative Urban-Environmental Intelligence
  11. Quantum Computing for Augmenting AI, Machine Learning, and Generative AI in Smarter Eco-Cities: Innovative Solutions for Environmental Sustainability and Infrastructure Optimization
  12. Quantum AI and Generative AI for Smarter Eco-City Development: A Unified Framework and Analysis of Deployment, Hardware, Algorithmic, Data, and Environmental Challenges

Product details

  • Edition: 1
  • Latest edition
  • Published: August 1, 2026
  • Language: English

About the author

SB

Simon Elias Bibri

Simon Elias Bibri, PhD, is a globally recognized scholar and expert in sustainable smart cities, smarter eco-cities, and environmental sustainability and resilience. He currently serves as a Senior Researcher and Project and Scientific Coordinator at the Swiss Federal Institute of Technology in Lausanne (EPFL). He has a diverse professional background, having served as Head of the Computer Department, Software and IT Business Engineer, IT Project Manager, Green ICT and Environmental Sustainability Strategist, Research Associate, Assistant Professor, and International Consultant. He has also been a visiting scholar at Lund University and a visiting senior researcher at the Royal Institute of Technology (KTH) in Sweden. He has served as an international expert in AI and Applied ML for Climate Action for the UNFCCC and in Sustainable Urban Development for UNIDO. Currently, he is an expert for the Focus Group on Smart Sustainable Cities, Environmental Sustainability, and Digital Twins at the ITU. He also serves as Editor-in-Chief of the International Journal of Environmental Studies at Taylor & Francis, Book Series Editor at Elsevier, Associate Editor of the Sustainable Cities and Society journal at Elsevier, and Lead Editor of the Sustainable Artificial Intelligence-Powered Applications book series at Springer. He holds a bachelor’s degree in Computer Engineering, multiple master’s degrees from Esteemed Swedish universities, and a PhD in Computer Science and Information Technology from NTNU. He is a prolific scholar with numerous highly cited journal articles, 10 authored books, 4 edited works, and 18 co‑edited volumes to his credit. His work has been cited over 18,000 times, resulting in an h-index of 60. His impact has been recognized by Stanford University and Elsevier as among the top 1% of scientists worldwide, a distinction he has held for six consecutive years. He has also been listed by ScholarGPS as the #1 highly ranked scholar in sustainable cities, #2 in urbanism, and #8 in environmental sustainability in the world. Recently, he joined an EU Horizon Europe consortium project as Scientific Coordinator, Senior Scientist, and WP leader.

Affiliations and expertise
Institute of Computer and Communication Sciences, School of Architecture, Civil and Environmental Engineering, Media and Design Laboratory, Swiss Federal Institute of Technology, Lausanne, Switzerland