Название: Fostering Machine Learning and IoT for Blockchain Technology: Smart Cities Applications, Volume 2
Автор: Khaleel Ahmad, Uma N. Dulhare, Mohammad Sufian Badar, Jameel Ahamed, M.A. Rizvi
Издательство: Springer
Серия: Transactions on Computer Systems and Networks
Год: 2025
Страниц: 311
Язык: английский
Формат: pdf (true), epub
Размер: 52.1 MB

The book covers Blockchain Technology and its emerging field by developing socio-economic systems viz. efficiently establishing transparency, trust, increasing utilization of various resources, and reducing costs. 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 dwells 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, agriculture, smart transport, smart water management, smart waste management, smart energy management, etc.

Drones have lots of uses in different areas, but merging them into city airspace brings unique challenges for navigation and traffic control. To tackle these issues, this chapter looks at mixing blockchain and machine learning with drone routing and navigation systems. It dives into two main topics: systems for decentralized drone traffic control and protocols for decentralized coordination, highlighting how blockchain can help drones in communication/routing. Next, it lays out a plan for using blockchain, machine learning, and adaptive routing and navigation together showing how these technologies might team up to make drone operations better. Also, it aims to shed light on the hurdles of blending blockchain with drone navigation networks and the snags that arise when creating and rolling out machine-learning-based drone navigation systems. Some key issues covered include handling data in real-time growth of the system, keeping things private and secure, making different systems work together, following rules, saving energy, and limits on processing real drone data, plus factors like the environment, dynamic cityscapes, and bringing data together. By taking a deep look at these challenges, this chapter gives valuable insights and useful tips for people working on or studying drone navigation to attain sustainable growth in the smart city environment.