AI-Driven Strategies for Inclusive and Sustainable Urbanization by Mazni Omar (Hardback)

£190.00
Available
Product Ref. (e.g. ISBN, SKU)
9781041048725
Published:
21 Oct 2025
Format:
Hardback
Number of pages:
358 pages
Dimensions:
234mm
Weight:
0.000kgs
Author:
This book studies how AI technologies can be utilized to tackle the complex challenges encountered in urban areas, spanning from ethical, social, and environmental implications across urban governance and beyond.
This book explores the transformative potential of artificial intelligence (AI) in reshaping urban development practices. Its objective is to provide a comprehensive overview of the latest advancements in AI-driven strategies for urban development and governance, with a focus on promoting inclusivity, sustainability, and resilience in cities worldwide. This book studies how AI technologies can be utilized to tackle the complex challenges encountered in urban areas, spanning from ethical, social, and environmental implications across urban governance and beyond.The in-depth analysis in this book uncovers the potential of AI in addressing longstanding challenges and seizing new opportunities in urban contexts, offering insights into wide-ranging applications. For the use of AI in urban planning, the authors showcase applications which help reduce environmental impact while enhancing accessibility for underserved communities by analysing real-time data on land use, transportation, and population needs. Another topic in the book examines AI-powered urban mobility systems, utilizing software that integrates real-time data to create adaptive transportation networks. These systems offer efficient, eco-friendly travel solutions tailored to diverse populations, including individuals with disabilities, by dynamically adjusting routes and services. Additionally, the book delves into digital inclusion and accessible technologies in smart cities, highlighting software that prioritizes accessibility and digital inclusion, ensuring that all residents, regardless of ability, can fully participate in urban life. The interdisciplinary approach allows readers to understand how different field, such as technology, urban planning, and social policy are intersecting to shape AI-driven urban development. By weaving together insights from these diverse areas, the book demonstrates how AI can address real-world challenges, from improving infrastructure to fostering sustainability and inclusivity in cities. This perspective helps readers grasp the broader impact of AI, showing how it can enhance various aspects of urban life, including social equity and environmental resilience.Through interdisciplinary research, case studies, and expert insights, the book aims to educate students in higher learning and inspire policymakers, urban planners, and practitioners to leverage AI technologies to tackle urban challenges and build better cities for all residents.

About the Author: Mazni Omar is an Associate Professor at the School of Computing, Universiti Utara Malaysia (UUM), with over 20 years of experience in academia. She is professionally certified in software testing (CTFL and CTFL-AT), with research interests in agile project management, software process and quality, and AI-driven predictive modeling. Her work has been widely published in reputable journals, conference proceedings, and book chapters. She has secured research grants from national, international, and industry bodies, and actively collaborates in Erasmus+ CBHE and KA107 Mobility Projects with institutions in Asia and Europe. She has received numerous accolades, including the Tom Craskadon Award (2017), Prolific Authors Award (2024), Best Researcher Award at the School of Computing (2023), and multiple awards at the Innovative Research, Invention, and Application Exhibition (IRIA) in 2022.Samsul Ariffin Abdul Karim is an Associate Professor at the School of Quantitative Sciences, Universiti Utara Malaysia (UUM), recognized for his extensive contributions to research and academic publishing. He is a registered Professional Technologist with the Malaysia Board of Technologists (MBOT) and specializes in areas such as numerical analysis, machine learning, optimization, and wavelets. He has authored over 200 publications, including 80 book chapters, 15 books with renowned publishers such as Springer and CRC Press, and five edited conference volumes. His excellence in education and research has been recognized with multiple awards, including the Effective Education Delivery Award and Publication Awards at UTP Quality Day (2010-2012), and the Book Publication Award in 2020. He also holds certification as a Wolfram Technology Associate.Amirulikhsan Zolkafli is a Senior Lecturer at the School of Computing, Universiti Utara Malaysia (UUM), specializing in Geographic Information Systems (GIS) and Information Technology. He holds a PhD in GIS from The University of Queensland, Australia. His research focuses on participatory GIS and practical applications across various domains, with numerous publications in reputable journals. He is part of an Erasmus+ team that developed a Master's programme in Geoinformatics for Disaster Risk Reduction. In addition to his academic work, he is actively involved in teaching, mentoring, and community service, bridging theory with real-world impact.Mazida Ahmad is an Associate Professor at the School of Computing, Universiti Utara Malaysia (UUM), with over 15 years of academic experience. Her teaching expertise spans Advanced Systems Analysis and Design, IT Project Management, Knowledge Management, and Information System Development. Her research interests include Knowledge Management, Software Engineering, and the use of IT in education. She is actively engaged in international collaborations, including research partnerships with Universitas Komputer Indonesia, Telkom University, and Universitas Kuningan, as well as involvement in the International Credit Mobility (ICM) program with University of West Attica, Greece, and a Capacity Building in Higher Education (CBHE) project with European and Asian institutions.

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Number of pages 358

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