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Smart city article details
| Title | Blockchain For Internet Of Things And Machine Learning-Based Automated Sectors |
|---|---|
| ID_Doc | 12455 |
| Authors | Tyagi A.K.; Kumari S.; Tiwari S. |
| Year | 2025 |
| Published | Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing |
| DOI | http://dx.doi.org/10.1002/9781394303601.ch9 |
| Abstract | The convergence of Blockchain technology with the Internet of Things (IoT) and Machine Learning (ML) heralds a transformative era for automated sectors. This chapter discusses the integration of Blockchain to fortify the security, transparency, and efficiency of data transactions within IoT networks and the application of ML algorithms in automating decision-making processes. The convergence of Blockchain and IoT addresses inherent challenges of data integrity and security in the large ecosystem of interconnected devices. By using distributed ledger principles, this synergy ensures tamper-resistant record-keeping, secure data sharing, and streamlined communication protocols. The result is a robust foundation for reliable and trustful interactions between IoT devices, mitigating vulnerabilities, and enhancing the overall resilience of automated systems. Furthermore, the integration of ML algorithms into automated sectors opens avenues for intelligent decision-making, predictive analytics, and optimization. This chapter investigates how Blockchain, as a secure and transparent data layer, facilitates the training and deployment of ML models by providing a trustworthy data source and an immutable audit trail for model outcomes. In this chapter, real-world applications and case studies will be examined to illustrate the impact of this triad - Blockchain, IoT, and ML - on diverse sectors such as smart cities, industrial automation, and healthcare. We also discuss challenges and opportunities arising from this integration, including scalability, interoperability, and ethical issue. By keeping light on the symbiotic relationship between Blockchain, IoT, and ML in automated sectors, this chapter aims to contribute to a deeper understanding of the technological advancements shaping the future of intelligent, secure, and efficient automated systems. © 2024 Scrivener Publishing LLC. |
| Author Keywords | Automated sectors; Blockchain; Data integrity; Internet of Things (IoT); Machine learning (ML); Predictive maintenance |
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