Data-driven mining, learning and analytics for secured smart cities : trends and advances

Data-driven mining, learning and analytics for secured smart cities : trends and advances / Chinmay Chakraborty, Jerry Chun-Wei Lin, Mamoun Alazab, editors.

This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, servi...

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Bibliographic Details
Other Authors: Chakraborty, Chinmay (Editor), Lin, Jerry Chun-Wei (Editor), Alazab, Mamoun, 1980- (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, [2021]
Series:Advanced sciences and technologies for security applications,
Subjects:
Smart cities.
Data mining.
Municipal engineering > Data processing.
City planning > Data processing.
City planning > Data processing
Data mining
Municipal engineering > Data processing
Smart cities
Online Access:Click for online access
Description
Summary:This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.
Physical Description:1 online resource (x, 383 pages) : illustrations (some color)
Bibliography:Includes bibliographical references.
ISBN:9783030721398
3030721396
ISSN:1613-5113
Source of Description, Etc. Note:Online resource; title from PDF title page (SpringerLink, viewed May 7, 2021).

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