Sustainable and Smart Cities: Ecological Design, Technological Innovation, and Climate Resilience
Produktnummer:
189e33b0db04364bb5ae48b3c8700ae4ae
Themengebiete: | Climate Change Micro-Segregation Social Equity Urban Automation Urban Climate Urban Design Urban Resilience |
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Veröffentlichungsdatum: | 26.10.2025 |
EAN: | 9783032005458 |
Sprache: | Englisch |
Seitenzahl: | 394 |
Produktart: | Unbekannt |
Herausgeber: | Amer, Mourad Bibri, Simon Elias Gökçe Özdamar, Esen |
Verlag: | Springer International Publishing |
Untertitel: | A Collection of Selected Papers From the Proceedings of Future Smart Cities (FSC-2024)- Morocco and Urban Regeneration and Sustainability (URS-2024)- Italy |
Produktinformationen "Sustainable and Smart Cities: Ecological Design, Technological Innovation, and Climate Resilience"
This book explores adaptive strategies that integrate Anthropogenic principles into architectural and urban design, particularly in low-income contexts like East Africa. It examines urban revitalization through case studies, such as Benghazi’s smart indicators, the use of public spaces for climate resilience, and transformative projects like reclaiming Lebanese quarries and understanding micro-segregation in Thessaloniki. Moreover, it emphasizes the role of eco-communities, post-pandemic urban design, and advanced spatial tools like BIM technology and robotic assembly. It also explores the potential of blockchain and 6G networks in advancing urban planning. This book also investigates AI-driven solutions for traffic management, accident prediction, and energy-efficient automated vehicle systems. It also envisions integrating autonomous aerial vehicles into smart city frameworks and explores collaborative platforms for research innovation. Last but not least, this book focuses on distributed energy systems, the electrification of transport, and innovative governance models like the Urban Climate Transition Governance Prism. It concludes with advanced techniques for environmental monitoring, such as cropland mapping using time-series data.

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