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{ "item_title" : "Big Data Analytics for Cyber-Physical Systems", "item_author" : [" Guido Dartmann", "Houbing Herbert Song", "Anke Schmeink "], "item_description" : "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 the implementation of machine learning algorithms in embedded systems, focusing on the interaction between IoT technology and the mathematical tools to evaluate the extracted data of those systems. Chapters provide different tools and applications on a broad list of data analytics and machine learning tools. Additionally, the book addresses how to incorporate these technologies into our society by examining new platforms for IoT in schools and new and necessary courses. As cyber-physical systems (CPS) and the Internet of Things (IoT) are rapidly developing technologies that are transforming our society, this book provides a timely update for both practitioners and interested researchers. Fills the gap between IoT, CPS and mathematical modelingIncludes numerous use cases that discuss how concepts are applied in different domains and applicationsProvides best practices, real developments and winning stories that complement technical informationUniquely covers concepts of mathematical foundations of signal processing and machine learning in CPS and IoT", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/0/12/816/637/0128166371_b.jpg", "price_data" : { "retail_price" : "125.00", "online_price" : "125.00", "our_price" : "125.00", "club_price" : "125.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Big Data Analytics for Cyber-Physical Systems|Guido Dartmann

Big Data Analytics for Cyber-Physical Systems : Machine Learning for the Internet of Things

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Overview

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 the implementation of machine learning algorithms in embedded systems, focusing on the interaction between IoT technology and the mathematical tools to evaluate the extracted data of those systems. Chapters provide different tools and applications on a broad list of data analytics and machine learning tools. Additionally, the book addresses how to incorporate these technologies into our society by examining new platforms for IoT in schools and new and necessary courses.

As cyber-physical systems (CPS) and the Internet of Things (IoT) are rapidly developing technologies that are transforming our society, this book provides a timely update for both practitioners and interested researchers.

  • Fills the gap between IoT, CPS and mathematical modeling
  • Includes numerous use cases that discuss how concepts are applied in different domains and applications
  • Provides "best practices," "real developments" and "winning stories" that complement technical information
  • Uniquely covers concepts of mathematical foundations of signal processing and machine learning in CPS and IoT

This item is Non-Returnable

Details

  • ISBN-13: 9780128166376
  • ISBN-10: 0128166371
  • Publisher: Elsevier
  • Publish Date: July 2019
  • Dimensions: 9 x 6 x 0.81 inches
  • Shipping Weight: 1.16 pounds
  • Page Count: 396

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