Fostering Machine Learning and IoT for Blockchain Technology

Springer, 2025

This book covers Blockchain Technology and its emerging field by developing socio-economic systems viz. efficiently establishing transparency, and trust, increasing utilization of various resources, and reducing cost. This book is organized into 2 volumes that provide an overview of Blockchain technology foundations of Blockchain, Machine Learning and Distributed Systems, Cryptography, Consensus algorithm, Bitcoin concepts, and its properties, Smart Contracts, developing knowledge of tools like Hyperledger, Multichain, Ethereum, etc. Machine learning algorithms, applications of a smart city using machine learning and blockchain technology. While this book will dwell on the foundations of Blockchain Technology as a part of transparency, scalability, integrity, security, and how the machine learning algorithms integrate with blockchain technology-based smart city applications, it will also focus on contemporary topics for Research and Development in various sectors. With an in-depth knowledge of the technology underlying various platforms such as Bitcoin, Ethereum, and Hyperledger. As a beginner, the reader will be learning the importance of consensus in transactions, how transactions are stored on Blockchain & how to use it in the financial domain, such as virtual currency, cross-border payment and settlement bills and supply chain finance, securities insurance, and transactions viz. Bitcoin. The reader will be able to develop custom smart contracts using solidity and Remix IDE using the Ethereum platform and deploy them on the test Blockchain network using Truffle. The reader will learn how to build a machine learning model and analyze the data which is generated by the practical use cases of Blockchain in various smart cities sectors like Smart Health, Smart food, and agriculture, smart transport, smart water management, smart waste management, smart energy management, etc.

• Curatore: Mohammad "Sufian" Badar, M. A. Rizvi, Jameel Ahamed, Khaleel Ahmad
• Anno edizione: 2025
• Editore: Springer
• Formato: EPUB3 con Adobe DRM
• Lingua: Inglese
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9789819640782