Machine Learning Adoption in Blockchain-Based Intelligent Manufacturing: Theoretical Basics, Applications, and Challenges (Intelligent Manufacturing and Industrial Engineering)

Description

This book looks at industry change patterns and innovations (such as artificial intelligence, machine learning, big data analysis, and blockchain support and efficiency technology) that are speeding up industrial transformation, industrial infrastructure, biodiversity, and productivity. This bookfocuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing. It also offers insights into manufacturing, logistics, and supply chain, where systems have undergone an industrial transformation. It discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure. It goes on to cover the effects that the Fourth Industrial Revolution has on industrial infrastructures and looks at the current industry change patterns and innovations that are accelerating industrial transformation activities. Researchers, scholars, and students from different countries will appreciate this book for its real-world applications and knowledge acquisition. This book targets manufacturers, industry owners, product developers, scientists, logistics, and supply chain engineers. Focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturingOffers insights into manufacturing, logistics, and supply chain where systems have undergone an industrial transformationDiscusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposureCovers the effects that the 4th Industrial Revolution has on industrial infrastructuresLooks at industry change patterns and innovations that are speeding up industrial transformation activities Om Prakash Jena is currently working as an associate professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India. Sabyasachi Pramanik is an assistant professor in the Department of Computer Science and Engineering, Haldia Institute of Technology, India. Ahmed A. Elngar is an associate professor in the Faculty of Computers & Artificial Intelligence, Beni-Suef University, Egypt. He is also an associate professor in the College of Computer Information Technology, chair of the Scientific Innovation Research Group (SIRG), and director of the Technological and Informatics Studies Center (TISC), American University in the Emirates, United Arab Emirates. Cover Half Title Series Title Copyright Contents Preface Editors Chapter 1 Integration of Big Data, Machine Learning, and Blockchain Technology Chapter 2 Blockchain in Digital Libraries: State of the Art, Trends, and Challenges Chapter 3 An Integration of Blockchain and Machine Learning into the Health Care System Chapter 4 Blockchain for the Industrial Internet of Things Chapter 5 Security Measures for Blockchain Technology Chapter 6 An Analysis of Data Management in Industry 4.0 Using Big Data Analytics Chapter 7 Exploring Role of Industry 4.0 Techniques for Building a Promising Circular Economy Concept: Manufacturing Industry Perspective Chapter 8 Comparative Analysis of Blockchain-Based Consensus Algorithms for Suitability in Critical IoT Infrastructures Chapter 9 Quantum Machine Learning and Big Data for Real-Time Applications: A Review Chapter 10 Sensors-Based Automatic Human Body Detection and Prevention System to Avoid Entrapment Casualties inside a Vehicle Chapter 11 A Mechanism to Protect Decentralized Transaction Using Blockchain Technology Index