Large Language Models for Sustainable Urban Development
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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…mehr

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Produktbeschreibung
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 integratingAI 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.
Autorenporträt
Nitin Liladhar Rane serves as an Associate Editor for Frontiers in Education, and a reviewer for Taylor and Francis journals such as Asian Architecture and Building Engineering, Architectural Engineering and Design Management, Advances in Materials and Processing Technologies, Journal of Human-Computer Interaction, Cogent Engineering, Cogent Education, and Automatika. He has authored more than 40 research papers in various international journals, including Springer, Elsevier, Taylor and Francis with over 4500 citations to his name. He serves as a project evaluator for the MUNIS BIRD Programme, implemented by the World bank and the Ministry of Higher Education, Science and Innovations. His research focuses on material characterization, structural analysis, resilient environments, urban planning, remote sensing, GIS, and environmental monitoring and assessment. Dr. Suraj Kumar Mallick is an Assistant Professor at the Department of Geography, Shaheed Bhagat Singh College, University of Delhi, New Delhi with a PhD degree in Urban Planning from Vidyasagar University. Before joining the faculty position, he was a Research Associate in the Department of Geography, Delhi School of Economics (DSE), University of Delhi, New Delhi. Later he joined as a Post-Doctoral Fellow of Centre for Technology Alternatives for Rural Areas (CTARA), Indian Institute of Technology, Bombay.  Prof. Jayesh Rane is Assistant Professor at Pillai HOC College of Engineering and Technology. His areas of interests include Image and Video processing, Artificial Intelligence and Internet of Things. He is author of Person Identification System using Handwritten signatures by ANN - A Neural Network Perspective (LAP Academic Publishing).  He is a member of National Apex Professional body of Electronics and Telecommunication, Computer Science and IT Professionals (IETE) and Indian Society for Technical Education (ISTE) professional societies.  Dr. Chaitanya B. Pande is a Research Fellow at the International University. His research interests include remote sensing, GIS, Google Earth Engine, machine learning, watershed management, hydrogeology, hydrological modelling, drought monitoring, land use and land cover analysis, groundwater quality, urban planning, hydro-geochemistry, groundwater modelling, geology, hyperspectral remote sensing, remote sensing and GIS application in natural resources management, watershed management and environmental monitoring and assessment subjects.