Overview
- Combines interdisciplinary expertise in the subject matter
- Offers a platform on multivariate information presented
- Presents concepts, research results, ideas and methods to explore a more complete picture of the interconnection
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 186)
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About this book
This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities.
Special features include:
- New research on the design of city elements and smart systems with respect to new technologies and scientific thinking
- Discussions on the theoretical background that lead to smart cities for the future
- New technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environments
The book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.
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Keywords
- smart cities
- artificial intelligence
- machine learning
- optimization
- sustainability
- mathematical applications
- environmental design
- sensors and actuators
- tools smart city design
- smart cities
- sustainable architecture
- autopoietic systems
- neoteric history
- cross-domain landscape
- ICT services
- electric vehicle sharing
- fog computing
- edge computing
Table of contents (11 chapters)
Reviews
Editors and Affiliations
About the editors
Panos M. Pardalos serves as distinguished professor of industrial and systems engineering at the University of Florida. Additionally, he is the Paul and Heidi Brown Preeminent Professor of industrial and systems engineering. Professor Pardalos is also an affiliated faculty member of the computer and information science department, the Hellenic Studies Center, and the biomedical engineering program. Additionally, he serves as the director of the Center for Applied Optimization. Professor Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, ecommerce, data mining, biomedical applications, and massive computing. Panos Pardalos is a prolific author who lectures all over the world. He is the recipient of a multitude of fellowships and awards, the most recent of which is the Humboldt Research Award (2018).
Stamatina Th. Rassia is an architect engineer holding a diploma in Architecture Engineering from the National Technical University of Athens (NTUA) in Greece. She has an MPhil in Environmental Design in Architecture and a PhD in Architecture from the University of Cambridge in the United Kingdom. Dr. Rassia is an expert on topics of sustainability and public health promotion by architectural design.
Arsenios Tsokas holds a BSc in Mathematics from the Aristotle University of Thessaloniki in Greece and a PhD in Industrial & Systems Engineering from the University of Florida in USA. He has a diverse background including data analysis, optimization, and machine learning.
Bibliographic Information
Book Title: Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities
Book Subtitle: Designing for Sustainability
Editors: Panos M. Pardalos, Stamatina Th. Rassia, Arsenios Tsokas
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-030-84459-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-84458-5Published: 10 January 2022
Softcover ISBN: 978-3-030-84461-5Published: 11 January 2023
eBook ISBN: 978-3-030-84459-2Published: 09 January 2022
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: VIII, 235
Number of Illustrations: 11 b/w illustrations, 65 illustrations in colour
Topics: Optimization, Machine Learning, Sustainable Architecture/Green Buildings, Artificial Intelligence