Dewey Class |
519.6 |
Title |
Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities ( EBook) : Designing for Sustainability / / edited by Panos M. Pardalos, Stamatina Th. Rassia, Arsenios Tsokas. |
Added Personal Name |
Pardalos, Panos M. |
Rassia, Stamatina Th |
Tsokas, Arsenios |
Other name(s) |
SpringerLink (Online service) |
Edition statement |
1st ed. 2022. |
Publication |
Cham : : Springer International Publishing : : Imprint: Springer, , 2022. |
Physical Details |
VIII, 235 p. 76 illus., 65 illus. in color. : online resource. |
Series |
Springer Optimization and Its Applications 1931-6836 ; ; 186 |
ISBN |
9783030844592 |
Summary Note |
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.: |
Contents note |
Cities as Convergent Autopoietic Systems (V. Dobrev) -- Digital ‘Vitalism’ and its ‘Epistemic’ Predecessors: ‘Smart’ Neoteric History and Contemporary Approaches (Moraitis) -- Unbuildable Cities (Th. Rassia) -- Smart Cities as Identities (Tsoniotis) -- A Cross-domain Landscape of ICT Services in Smart Cities (Bunhova) -- A Novel Data Representation Method for Smart Cities’ Big Data (N. Nagy) -- A Pedestrian Level Strategy to Minimize Outdoor Sunlight Exposure (X. Li) -- Planning and Management of Charging Facilities for Electric Vehicle Sharing (W. Qi) -- A Reactive Architectural Proposal for Fog/edge Computing in the Internet of Things Paradigm with Application in Deep Learning (Belmonte-Fernandez) -- Urban Big Data: City Management and Real Estate Markets (Saiz) -- Social Media-based Intelligence for Disaster Response and Management in Smart Cities (Khatoon). |
Mode of acces to digital resource |
Digital reproduction.- |
Cham : |
Springer International Publishing, |
2022. - |
Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format. |
System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
Internet Site |
https://doi.org/10.1007/978-3-030-84459-2 |
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