Big Data Analytics for Cyber-Physical Systems

Download or Read eBook Big Data Analytics for Cyber-Physical Systems PDF written by Guido Dartmann and published by Elsevier. This book was released on 2019-07-15 with total page 396 pages. Available in PDF, EPUB and Kindle.
Big Data Analytics for Cyber-Physical Systems
Author :
Publisher : Elsevier
Total Pages : 396
Release :
ISBN-10 : 9780128166376
ISBN-13 : 0128166371
Rating : 4/5 (76 Downloads)

Book Synopsis Big Data Analytics for Cyber-Physical Systems by : Guido Dartmann

Book excerpt: Cyber-physical systems (CPS) and the Internet of Things (IoT) are rapidly developing technologies that are transforming our society. The disruptive transformation of the economy and society is expected due to the data collected by these systems, rather than the technological aspects of such as networks, embedded systems, and cloud technology. However, to create value out of the data, it must be transformed into information and therefore, expertise in data analytics and machine learning is the key component of future smart systems in cities and other applications. Big Data Analytics in Cyber-Physical Systems 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 to evaluate the extracted data of those systems. Each chapter provides different tools and applications in order to present a broad list of data analytics and machine learning tools in multiple IoT applications. Additionally, this volume addresses the education 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. Fills the gap between IoT, CPS, and mathematical modeling Numerous use cases that discuss how concepts are applied in different domains and applications Provides "best practices," "real developments", and "winning stories" to complement technical information Uniquely covers contents within the context of mathematical foundations of signal processing and machine learning in CPS and IoT


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