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Large Language Models for Sustainable Urban Development.

Large Language Models for Sustainable Urban Development.

・ISBN 978-3-031-86041-6 paper EUR 199.99

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お気に入り
著者・編者Rane, Nitin Liladhar / Mallick, Suraj Kumar / Rane, Jayesh / Pande, Chaitanya Baliram (eds.),
シリーズ (The Springer Series in Applied Machine Learning)
出版社 (Springer International Publishing AG, SZ)
出版年月2026
ページ数454 pp.
言語ENG
ニュース番号<A05-90451>

解説

With rapid urbanization defining the 21st Century, cities face mounting challenges in achieving sustainability, equity, and functionality. This book explores how innovative technologies such as Artificial Intelligence (AI) and Large Language Models (LLMs) can transform urban development by offering intelligent, data-driven solutions. LLMs go beyond automation, acting as co-creators in addressing environmental sustainability, resource management, and equitable development. By analyzing regulations, best practices, and real-time data on phenomena such as air pollution and traffic, these models empower urban planners to design smarter, more sustainable cities while fostering collaboration across disciplines.

Divided into five sections, the book explores the diverse applications of LLMs, from optimizing renewable energy systems and enhancing urban planning to revolutionizing construction practices and improving resource efficiency. It highlights case studies on integrating AI with smart infrastructure, ecological balance, and disaster resilience. While underscoring their transformative potential, the book also examines ethical considerations such as bias, privacy, and environmental impact. More than a collection of research, this work is a call to action for urban planners, data scientists, policymakers, and researchers to harness AI responsibly in building greener, more equitable urban futures.