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.
Format:
CONTRIBUTORS: Guido Dartmann, Houbing Song, Anke Schmeink
EAN: 9780128166376
COUNTRY: United States
PAGES:
WEIGHT: 660 g
HEIGHT: 229 cm
PUBLISHED BY: Elsevier Science Publishing Co Inc
DATE PUBLISHED: 2019-07-16
CITY:
GENRE: LAW / General, LAW / Transportation
WIDTH: 152 cm
SPINE:
Book Themes:
Transport law
Prof. Dr.-Ing. Guido Dartmann is a professor and research group leader at Trier University of Applied Sciences, Germany. Dr. Dartmann also serves as a co-lead of the German IoT expert group of national Digital Summit. His research interests include distributed systems, data analytics, signal processing, optimization of technical systems, cyber-physical systems, wireless communication, cyber-security, internet of things, and traffic and mobility. Houbing Song, PhD, is an assistant professor of Electrical Engineering and Computer Science and the director of the Security and Optimization for Networked Globe Laboratory (SONG Lab) at the Embry-Riddle Aeronautical University, Florida, United States. His research interests include cyber-physical systems, cybersecurity and privacy, IoT, big data analytics, connected vehicles, smart health, wireless communications, and networking. Dr. Song has edited and authored several books in the field, including Cyber-Physical Systems: Foundations, Principles and Applications published by Elsevier. Prof. Dr.-Ing. Anke Schmeink, is a professor leading the ISEK research and teaching area at RWTH Aachen University, Germany. Her research interests include information theory and network optimization.
