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Large Language Models for Sustainable Urban Development

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Large Language Models for Sustainable Urban Development Synopsis

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.

About This Edition

ISBN: 9783031860386
Publication date:
Author: Nitin Liladhar Rane, Suraj Kumar Mallick, Jayesh Rane, Chaitanya Baliram Pande
Publisher: Springer an imprint of Springer Nature Switzerland
Format: Hardback
Pagination: 445 pages
Series: The Springer Series in Applied Machine Learning
Genres: Artificial intelligence
Natural language and machine translation
City and town planning: architectural aspects
Regional, state and other local government

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