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Название: Industry 4.0 Interoperability, Analytics, Security, and Case Studies
Автор: G. Rajesh, X. Mercilin Raajini
Издательство: CRC Press
Серия: Big Data for Industry 4.0: Challenges and Applications
Год: 2021
Страниц: 332
Язык: английский
Формат: pdf (true), epub
Размер: 12.9 MB
All over the world, vast research is in progress on the domain of Industry 4.0 and related techniques. Industry 4.0 is expected to have a very high impact on labor markets, global value chains, education, health, environment, and many social economic aspects. Industry 4.0 Interoperability, Analytics, Security, and Case Studies provides a deeper understanding of the drivers and enablers of Industry 4.0. It includes real case studies of various applications related to different fields, such as cyber physical systems (CPS), Internet of Things (IoT), cloud computing, Machine Learning, virtualization, decentralization, blockchain, fog computing, and many other related areas. Also discussed are interoperability, design, and implementation challenges. Big Data Analytics (BDA) can be referred to as “the process of analyzing large scale datasets in order to find unknown correlations, hidden patterns, and other valuable information which is not able to be analysed using conventional data analytics”, as the conventional data analysis techniques are no longer effective because of the special characteristics of big dаta: massive, heterogeneous, high dimensional, complex, erroneous, unstructured, noisy, and incomplete.
Автор: G. Rajesh, X. Mercilin Raajini
Издательство: CRC Press
Серия: Big Data for Industry 4.0: Challenges and Applications
Год: 2021
Страниц: 332
Язык: английский
Формат: pdf (true), epub
Размер: 12.9 MB
All over the world, vast research is in progress on the domain of Industry 4.0 and related techniques. Industry 4.0 is expected to have a very high impact on labor markets, global value chains, education, health, environment, and many social economic aspects. Industry 4.0 Interoperability, Analytics, Security, and Case Studies provides a deeper understanding of the drivers and enablers of Industry 4.0. It includes real case studies of various applications related to different fields, such as cyber physical systems (CPS), Internet of Things (IoT), cloud computing, Machine Learning, virtualization, decentralization, blockchain, fog computing, and many other related areas. Also discussed are interoperability, design, and implementation challenges. Big Data Analytics (BDA) can be referred to as “the process of analyzing large scale datasets in order to find unknown correlations, hidden patterns, and other valuable information which is not able to be analysed using conventional data analytics”, as the conventional data analysis techniques are no longer effective because of the special characteristics of big dаta: massive, heterogeneous, high dimensional, complex, erroneous, unstructured, noisy, and incomplete.