Big data analytics for cyber-physical systems : machine learning for the internet of things

Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, IoT gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interacti...

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Bibliographic Details
Main Authors: Dartmann, Guido, Song, Houbing, Schmeink, Anke
Format: eBook Book
Language:English
Published: Amsterdam Elsevier 2019
Edition:1
Subjects:
Big data
Big data > Data processing
Embedded computer systems
Internet of things
Machine learning
ISBN:9780128166376, 0128166371
Online Access:Get full text
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Summary:Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, IoT gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interaction between IoT technology and the mathematical tools used to evaluate the extracted data of those systems. Each chapter provides the reader with a broad list of data analytics and machine learning methods for multiple IoT applications. Additionally, this volume addresses the educational transfer needed to incorporate these technologies into our society by examining new platforms for IoT in schools, new courses and concepts for universities and adult education on IoT and data science. .
Bibliography:Includes bibliographical references and index
ISBN:9780128166376
0128166371
DOI:10.1016/C2018-0-00208-X