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Next Generation Data Science and Blockchain Technology for Industry 5.0: Concepts and Paradigms

Next Generation Data Science and Blockchain Technology for Industry 5.0: Concepts and Paradigms

Hardcover

General ComputersComputer Security

ISBN10: 1394245181
ISBN13: 9781394245185
Publisher: Wiley-IEEE Press
Published: Jul 29 2025
Pages: 496
Weight: 1.83
Height: 1.06 Width: 6.00 Depth: 9.00
Language: English

A groundbreaking view of the industrial models of the future

Industry 5.0 is an increasingly widespread term for the coming business paradigm, which will combine humans, robotics, and smart technology to create the industrial processes of the future. Technological innovations like smart factories, networked processes, data science, Blockchain, and more will be combined to revolutionize industry and drive innovation at an unprecedented pace. Innovation-minded knowledge workers will be increasingly forced to grapple with challenging questions in order to meet the demands, and exploit the opportunities, of this groundbreaking paradigm.

Next Generation Data Science and Blockchain Technology for Industry 5.0 offers an overview of these most important questions, their early answers, and the most promising paths forward. Incorporating practical case studies grounded in real-world data, the book emphasizes a hands-on approach combining numerous analytical tools. With a broad view of the historical role of industrial revolutions and a cutting-edge grasp of the key technologies, this book is an indispensable window into the future of business.

Next Generation Data Science and Blockchain Technology for Industry 5.0 readers will also find:

  • Incorporation of tools including statistical analysis, machine learning, graph analysis, and more
  • Detailed treatment of cutting-edge technologies like additive manufacture (3D printing), edge computing, and many others
  • Self-assessment tools to facilitate understanding

Next Generation Data Science and Blockchain Technology for Industry 5.0 is ideal for academics, researchers, and advanced students in Computer Science and Computer Technology, as well as professionals and researchers working in Data Science or any other area of industrial technology.

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