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Machine learning for smart environments/citiesan IoT approach /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning for smart environments/citiesedited by Goncalo Marques, Alfonso Gonzalez-Briones, Jose Manuel Molina Lopez.
Reminder of title:	an IoT approach /
other author:	Marques, Goncalo.
Published:	Cham :Springer International Publishing :2022.
Description:	xx, 243 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Smart cities.
Online resource:	https://doi.org/10.1007/978-3-030-97516-6
ISBN:	9783030975166$q(electronic bk.)

Machine learning for smart environments/citiesan IoT approach /
Machine learning for smart environments/citiesan IoT approach /[electronic resource] :edited by Goncalo Marques, Alfonso Gonzalez-Briones, Jose Manuel Molina Lopez. - Cham :Springer International Publishing :2022. - xx, 243 p. :ill. (some col.), digital ;24 cm. - Intelligent systems reference library,v. 1211868-4408 ;. - Intelligent systems reference library ;v.24..

An Introduction and Systematic Review on Machine Learning for Smart Environments/Cities: An IoT Approach -- Model-Based Digital Threads for Socio-Technical Systems -- IoT Regulated Water Quality Prediction Through Machine Learning for Smart Environments.

This book introduces machine learning and its applications in smart environments/cities. At this stage, a comprehensive understanding of smart environment/city applications is critical for supporting future research. This book includes chapters written by researchers from different countries across the globe and identifies critical threads in research and also gaps that open up new and challenging lines of research for the future. Recent advances are discussed, and thorough reviews introduce readers to critical domains. The discussion on key research topics presented in this book accelerates smart city and smart environment implementations based on IoT technologies. Consequently, this book supports future research activities aimed at developing future IoT architectures for smart environments/cities.

ISBN: 9783030975166$q(electronic bk.)

Standard No.: 10.1007/978-3-030-97516-6doiSubjects--Topical Terms:

820761
Smart cities.

LC Class. No.: TD159.4 / .M33 2022

Dewey Class. No.: 307.760285

Machine learning for smart environments/citiesan IoT approach /
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505 0 $a An Introduction and Systematic Review on Machine Learning for Smart Environments/Cities: An IoT Approach -- Model-Based Digital Threads for Socio-Technical Systems -- IoT Regulated Water Quality Prediction Through Machine Learning for Smart Environments.
520 $a This book introduces machine learning and its applications in smart environments/cities. At this stage, a comprehensive understanding of smart environment/city applications is critical for supporting future research. This book includes chapters written by researchers from different countries across the globe and identifies critical threads in research and also gaps that open up new and challenging lines of research for the future. Recent advances are discussed, and thorough reviews introduce readers to critical domains. The discussion on key research topics presented in this book accelerates smart city and smart environment implementations based on IoT technologies. Consequently, this book supports future research activities aimed at developing future IoT architectures for smart environments/cities.
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