Randhir Kumar – författare

This book reviews research works in recent trends in blockchain, AI, and Digital Twin based IoT data analytics approaches for providing the privacy and security solutions for Fog-enabled IoT networks. Due to the large number of deployments of IoT devices, an IoT is the main source of data and a very high volume of sensing data is generated by IoT systems such as smart cities and smart grid applications. To provide a fast and efficient data analytics solution for Fog-enabled IoT systems is a fundamental research issue. For the deployment of the Fog-enabled-IoT system in different applications such as healthcare systems, smart cities and smart grid systems, security, and privacy of big IoT data and IoT networks are key issues. The current centralized IoT architecture is heavily restricted with various challenges such as single points of failure, data privacy, security, robustness, etc.This book emphasizes and facilitates a greater understanding of various security and privacy approaches using the advances in Digital Twin and Blockchain for data analysis using machine/deep learning, federated learning, edge computing and the countermeasures to overcome these vulnerabilities.

This book reviews research works in recent trends in blockchain, AI, and Digital Twin based IoT data analytics approaches for providing the privacy and security solutions for Fog-enabled IoT networks. Due to the large number of deployments of IoT devices, an IoT is the main source of data and a very high volume of sensing data is generated by IoT systems such as smart cities and smart grid applications. To provide a fast and efficient data analytics solution for Fog-enabled IoT systems is a fundamental research issue. For the deployment of the Fog-enabled-IoT system in different applications such as healthcare systems, smart cities and smart grid systems, security, and privacy of big IoT data and IoT networks are key issues. The current centralized IoT architecture is heavily restricted with various challenges such as single points of failure, data privacy, security, robustness, etc.This book emphasizes and facilitates a greater understanding of various security and privacy approaches using the advances in Digital Twin and Blockchain for data analysis using machine/deep learning, federated learning, edge computing and the countermeasures to overcome these vulnerabilities.

In today’s rapidly evolving digital landscape, blockchain and artificial intelligence (AI) are at the forefront of transforming various industries, and education is no exception. The convergence of these two revolutionary technologies promises to reshape the modern education system by enhancing data security, promoting personalized learning, and creating decentralized frameworks for record-keeping and credentialing. This book delves into how blockchain and AI can drive a more inclusive, efficient, and secure educational ecosystem, where student-centered approaches and data integrity are paramount.This book is organized into several sections, each exploring the distinct roles of blockchain and AI within education. It begins with an introduction to the fundamental principles of these technologies and an overview of their individual strengths. Following this, chapters examine blockchain’s role in secure credential verification, decentralized learning platforms, and the protection of digital records. Next, the discussion shifts to AI applications, covering adaptive learning models, predictive analytics, and AI-driven administrative support. Finally, the book provides real-world case studies and future projections on how blockchain and AI together can tackle challenges in education, such as data privacy, resource distribution, and student engagement, ultimately creating an interconnected and resilient educational framework.This book is designed for educators, administrators, policymakers, technology enthusiasts, and researchers who are interested in the transformative potential of emerging technologies in education. It serves as a comprehensive guide for those looking to understand the practical applications and implications of blockchain and AI in the modern education system.

Blockchain and AI for Security and Privacy in Smart Agriculture provides an innovative outlook on how advanced technologies are redefining the future of farming. As smart agriculture increasingly integrates IoT devices, sensors, drones, and data analytics to enhance efficiency and sustainability, it also faces critical issues surrounding data privacy, security, and stakeholder trust. This book explores how blockchain and artificial intelligence (AI) effectively address these challenges. Blockchain’s decentralized and tamper-proof system ensures secure data storage, transparency in agricultural processes, and end-to-end traceability within the supply chain—from producers to consumers. AI further strengthens this ecosystem by offering intelligent threat detection, predictive analytics, and real-time decision-making to enhance crop management, optimize resources, and mitigate risks. Targeted toward researchers, academics, policymakers, agri-tech entrepreneurs, and industry experts, this book combines foundational theory with real-world applications, case studies, and practical implementation models. It equips readers with the knowledge to design secure, privacy-preserving, and trustworthy smart farming systems that enhance productivity, reduce fraud, and build a sustainable agricultural future.Key features:Focuses on the latest development in Blockchain and AI Analytics in Smart Agriculture.Presents different issues of Security and Privacy in Smart Agriculture.Offers the latest Blockchain and AI models for security analytics in Smart Agriculture.Discusses the emerging role of Blockchain and AI Enabled Analytics and Technologies in detection of threats in Smart Agriculture.Presents the prospects on Blockchain and AI based Smart Agriculture Data Analytics and decision-making model.