"Version: 20210205"--Title page verso.

Includes bibliographical references.

1. Internet of things (IoT) -- 1.1. IoT overview -- 1.2. IoT common uses -- 1.3. IoT--security -- 1.4. Functional view of IoT -- 1.5. Application domains -- 1.6. Summary

2. Industrial Internet of things -- 2.1. Industrial IoT overview -- 2.2. How does the IIoT system work? -- 2.3. IIoT advantages -- 2.4. IIoT versus IoT differences -- 2.5. IIoT vendors -- 2.6. Industrial IoT applications -- 2.7. Industrial IoT challenges -- 2.8. IIoT futures -- 2.9. Summary

3. Blockchain technology -- 3.1. Overview of blockchain -- 3.2. Public key cryptography (PKI) in the blockchain -- 3.3. Hashing -- 3.4. Bitcoin mining -- 3.5. Chaining blocks -- 3.6. Proof of work (PoW) -- 3.7. Bitcoin mining and network -- 3.8. Incentives to miners -- 3.9. Merkle tree of blockchain -- 3.10. Payment verification in blockchain -- 3.11. Conflicts resolution -- 3.12. Privacy in blockchain -- 3.13. Mitigating attacks on bitcoin -- 3.14. Conclusion

4. Blockchain key characteristics -- 4.1. Immutability -- 4.2. Decentralization -- 4.3. Improved safety -- 4.4. Distributed ledgers -- 4.5. Consensus -- 4.6. Quick solution -- 4.7. Summary

5. Smart contract -- 5.1. Overview of smart contract -- 5.2. Operating methods of smart contracts -- 5.3. Sites and programming languages -- 5.4. Features and the importance of smart contracts -- 5.5. Application views of smart contracts -- 5.6. Challenges -- 5.7. Current developments and upcoming trends of smart contracts -- 5.8. Advantages of smart contracts -- 5.9. Summary

6. Taxonomy of blockchain systems -- 6.1. Decentralized applications of AI -- 6.2. Decentralized operations -- 6.3. Blockchain types -- 6.4. Decentralized infrastructure for AI applications -- 6.5. Role of consensus protocols for AI appliances -- 6.6. Summary

7. Combination of blockchain and IIOT -- 7.1. Opportunities for integrating blockchain with IIoT -- 7.2. IIoT with blockchain combination (BIIoT) -- 7.3. Challenges at a blockchain-IIoT incorporation -- 7.4. BIIoT usage -- 7.5. Summary

8. BIIOT architecture -- 8.1. Architecture of BIIoT -- 8.2. Physical layer -- 8.3. Service layer of blockchain -- 8.4. BIIoT architecture execution procedure -- 8.5. Another dimension of BIIoT architecture -- 8.6. Summary

9. BIIOT deployment -- 9.1. General deployment of BIIoT -- 9.2. Deployment of BIIoT in smart industry -- 9.3. Key challenges of BIIoT -- 9.4. Summary

10. BIIOT applications -- 10.1. Smart manufacturing -- 10.2. Management of supply chain -- 10.3. Food industry -- 10.4. Smart grid -- 10.5. Health care -- 10.6. IoV and UAV -- 10.7. Retail and E-commerce industry -- 10.8. Summary.

Blockchain and the Internet of Things (IoT) are separately regarded as highly capable popular technologies. Blockchain is a database used for decentralized transaction purposes. It provides novel directions to store and manage data, whereas the IoT relates to the propagation of linked smart machines through the Internet. A technology significant to the manufacturing business, which is currently experiencing a digital revolution through new equipment and data, leading to the Industrial Internet of Things, or the IIoT. The IIoT has advanced swiftly, but privacy issues and safety vulnerabilities remain concerns. Incorporating blockchain technology with its decentralization and embedded cryptographic principles with the IIoT creates Blockchain for Industrial Internet of Things (BIIoT) which can overcome these security requirements and motivate the further development of Industry 4.0. This book gives a detailed survey of BIIoT and discusses all relevant aspects of this concept, including structural design and open research directions.

Industrial and academic researchers and engineers.

Also available in print.

Mode of access: World Wide Web.

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Lakshmana Kumar Ramasamy is currently associated with Hindusthan College of Engineering and Technology, India. He is also a Director-Research & Development (Artificial Intelligence) in a Canadian-based company (ASIQC) in Vancouver. He is the Founding Member of IEEE SIG of Big Data for Cyber Security and Privacy, IEEE. He is a global chapter Lead for MLCS [Machine Learning for Cyber Security]. He is involved in research and expertise in AI and Blockchain technologies and holds Data Science certification from John Hopkins University, United States. He also holds the Amazon Cloud Architect certification from Amazon Web Services. He holds the privileged Gold level partnership award from Infosys for bridging the gap between industry and academia in 2017. He holds the privileged Silver level partnership award from Infosys for bridging the gap between industry and academia in 2016. He is an Editor-In-Chief for Book Series, Advances in Quantum Computing, Artificial Intelligence, and Data Sciences for Industrial Transformation Series, and is also an Editor-In-Chief for Focus Series, Convergence of IoT and Blockchain Through Machine Learning Approaches, CRC Press. He is a core member of the Artificial Intelligence Editorial Advisory Board of Cambridge Scholars Publishing, UK. He is an Editorial board member of Trends in Renewable Energy Journal, USA and Frontiers in Communications and Networks, Switzerland. He is the Associate Editor for International Journal of Quality Control and Standards in Science and Engineering (IJQCSSE), IGI Publishers, USA. As part of his professional career, he has around 50+ publications in international journals and conferences. He has edited books published by Elsevier, CRC Press, Springer, and Wiley. He holds around 19 Indian patents and 2 International patents. He is an ACM Distinguished Speaker and IEEE brand ambassador. Seifedine Kadry has a bachelor's degree from Lebanese University, MS degree from Reims University (France) and EPFL (Lausanne), PhD from Blaise Pascal University (France), HDR degree (Habilitation) from Rouen University. At present, his research focuses on data science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing and ABET program evaluator for Engineering Tech. He is an IET Fellow. Currently, he is a full professor of data science at Noroff University College, Norway.

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