A comprehensive and practice-oriented exploration of blockchain technology, tracing its evolution from Bitcoin to Ethereum and beyond. This volume explains blockchain’s foundational principles, such as decentralization, immutability, and cryptographic security, before moving into real-world applications across finance, supply chain management, healthcare, governance, and emerging tech ecosystems. With contributions from leading researchers and practitioners, the book examines both opportunities and challenges ranging from scalability and energy consumption to regulatory clarity and security. Readers also gain insights into cutting-edge developments like smart contracts, decentralized finance (DeFi), identity systems, Layer 2 solutions, DAOs, and blockchain’s synergy with IoT and AI. Key Features Explains the core principles of blockchain, from decentralization to cryptographic security. Traces the evolution from Bitcoin and Ethereum to DeFi, smart contracts, and dApps. Demonstrates applications across finance, healthcare, supply chain, governance, and identity management. Addresses pressing challenges, including scalability, energy use, regulatory frameworks, and security threats. Explores future trends like interoperability, DAOs, Layer 2 solutions, and integration with IoT and AI.

Recent Advancements in Computational Intelligence: Concepts, Methodologies and Applications (Part 1) is an in-depth exploration of computational intelligence (CI), a rapidly evolving field blending artificial intelligence, machine learning, and data-driven problem-solving. The book focuses on biologically inspired methods such as neural networks, fuzzy logic, swarm intelligence, and evolutionary algorithms; it showcases how CI addresses complex real-world problems marked by uncertainty and incomplete data. Integrating theory with Industry 4.0 applications, the book spans diverse domains including healthcare, autonomous systems, cybersecurity, and smart computing. Structured across thematic sections like Social Computing, High-Performance Computing, Network Science, Smart Computing, and Intelligent Communications, it covers topics like deep learning for autonomous vehicles, AI-driven healthcare diagnostics, graph theory in cybersecurity, and reinforcement learning for generative AI. With contributions from international experts, it bridges foundational principles with applied research and case studies. Key Features: • Integrates emerging trends such as generative AI, edge computing, and reinforcement learning. • Demonstrates practical relevance through real-world case studies and industrial applications. • Promotes interdisciplinary understanding across computer science, engineering, and healthcare. • Provides actionable methodologies for researchers and practitioners advancing CI innovation. • Highlights the fusion of theory and practice in intelligent, adaptive systems.

Artificial Intelligence: Unleashing the Future builds a robust conceptual framework on artificial intelligence and machine learning before diving into practical applications. Beginning with a historical overview and foundational techniques in machine learning and deep learning the book’s chapters explore the deployment of AI in agriculture through smart irrigation, plant disease detection, and robotic farming; in cybersecurity via intelligent threat detection and defense tools; in healthcare through diagnostic AI, robotic surgery, and telemedicine; and in education by enabling personalized learning and adaptive technologies. Ethical, regulatory, and privacy concerns are also thoughtfully addressed, ensuring readers grasp both the opportunities and the complexities of AI integration. Key Features • Trace AI’s evolution and emerging architectures • Apply machine learning across real-world sectors • Explore sector-specific case studies and implementations • Understand ethical, legal, and data privacy issues • Gain insights into future trends in AI deployment.

A Primer on Wireless Technology and IoT Basics covers the journey of wireless networks from the early 1G systems to the anticipated capabilities of 6G, while also explaining essential wireless technologies such as GSM, WLAN, WPANs, MANETs, and Wireless Sensor Networks (WSNs). It further delves into how these technologies underpin IoT ecosystems, emphasizing their role in data collection, transmission, and smart system integration. Chapters explore key developments in wireless communication, types of networks, sensor architectures, IoT system layers, and real-world implementation challenges. Special attention is given to IoT applications across diverse sectors and how wireless protocols support their functionality. This book is particularly useful for readers seeking a strong foundational understanding of wireless systems and IoT, making it ideal for both technical and non-technical audiences. Key Features: Explain key generations of wireless technology from 1G to 6G. Clarify concepts related to GSM, WLAN, WPANs, MANETs, and WSNs Illustrate IoT architecture, protocols, and system layers Highlight real-world IoT use cases and applications Address implementation challenges and data handling in IoT systems

Digital Deception: Uncovering the Dark Side of AI in Social Networks is a critical investigation into how artificial intelligence silently influences, manipulates, and, at times, undermines digital interactions across social platforms. Bridging disciplines such as computer science, sociology, and ethics, the book exposes how AI technologies contribute to misinformation, surveillance, identity manipulation, and psychological exploitation in the digital sphere. With chapters on algorithmic bias, deep fakes, federated learning, and intrusion detection, the book reveals the hidden mechanisms that shape user behavior and societal discourse. It explores the ethical implications of AI-powered content curation, privacy violations, and the rise of automated cyberattacks-while proposing regulatory and technological countermeasures. Case studies and real-world examples illustrate the consequences of unchecked AI deployment and the erosion of trust in online spaces. Key features: Examines misinformation, digital surveillance, and algorithmic bias Presents real-world case studies and AI behavior models Highlights privacy concerns and ethical frameworks Proposes AI-driven defenses and user empowerment strategies

Beyond Blockchain: Reviewing the Impact and Evolution of Decentralized Networks (Part 2) continues the journey into the rapidly evolving world of blockchain and decentralized technologies. Building on the foundations laid in Part 1, this volume delves deeper into advanced applications such as decentralized finance (DeFi), decentralized identity systems, blockchain governance, and cross-chain interoperability. It also explores the future role of Web3, token economies, and data ownership in reshaping digital ecosystems. Designed for clarity and accessibility, the book simplifies complex ideas, enabling non-technical readers to grasp the broader implications of decentralization and its growing impact on business, governance, and daily life. Key Features: Explains DeFi, DAOs, and decentralized identity with clarity Explores cross-chain interoperability and next-gen blockchain tools Highlights blockchain’s role in shaping Web3 and digital governance Examines ethical implications and future regulatory landscapes Continuation of real-world case studies and thematic insights

Advances in AI for Financial, Cyber, and Healthcare Analytics: A Multidisciplinary Approach comprehensively explores how artificial intelligence and machine learning are reshaping decision-making, predictive modelling, and operational strategies across three critical sectors—finance, cybersecurity, and healthcare. Across nine chapters, the book delves into the foundations of financial analytics and explores AI’s role in market prediction, fraud detection, and risk analysis. It progresses into healthcare applications such as disease classification using ResNet, ethical implications of AI decisions, and the evolution of human-centred, edge-driven healthcare systems. In the cybersecurity domain, it addresses predictive threat modelling, smart home authentication, and biometric identification through advanced AI techniques. Key features: Unifies financial, healthcare, and cyber analytics through AI-driven solutions Demonstrates practical implementations with code examples and case studies Covers cutting-edge technologies like CNN-LSTM, attention models, and edge computing Addresses ethical, technical, and human-centred dimensions of AI

Analysis of Boundedness and Safeness in a Petri Net-Based Specification of Concurrent Control Systems provides a comprehensive study of concurrent control systems using Petri net models, with a focus on boundedness and safeness analysis. Designed for both academic and industry professionals, it bridges the gap between theoretical rigor and practical applications, offering essential insights for advancing knowledge in the field. The content covers foundational principles of control systems and Petri nets before exploring advanced analysis techniques. Topics include algorithms, computational complexity, and different Petri net classes. The book also addresses boundedness and safeness properties, presenting verification methods, case studies, and experimental results. Trends, challenges, and future directions are also discussed in the book equipping readers with practical tools to innovate in concurrent system design. Key Features: - In-depth coverage of Petri net-based concurrent system modeling and analysis. - Clear explanations supported by real-world examples and case studies. - A balanced approach combining theory and application.

Beyond Blockchain: Reviewing the Impact and Evolution of Decentralized Networks (Part 1) explores how blockchain and decentralized systems are transforming key industries and building a smarter, more connected world. The book covers practical applications such as Ethereum smart contracts in supply chains, blockchain for sustainable agriculture, climate monitoring, education, and revolutionizing healthcare, especially when combined with AI. Written in clear, simple language, it helps readers understand complex technologies without a technical background. Key Features: - Beginner-friendly guide to blockchain, smart contracts, and decentralized systems - Real-world use cases in supply chains, agriculture, education, and healthcare - Insights into integrating AI, IoT, and quantum computing with blockchain - Focus on sustainability, data security, and ethical tech use - Easy-to-read chapters with clear themes and practical insights.

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing industries, reshaping the way we interact with technology, and driving innovation across multiple disciplines. Advancements in Artificial Intelligence and Machine Learning is a comprehensive exploration of the latest developments, applications, and challenges in AI and ML, offering insights into cutting-edge research and real-world implementations. This book is a collection of twelve chapters, each exploring a distinct application of Artificial Intelligence (AI) and Machine Learning (ML). It begins with an overview of AI’s transformative role in Next-Gen Mechatronics, followed by a comprehensive review of key advancements and trends in the field. The book then examines AI’s impact across diverse sectors, including energy, digital communication, and security, with topics such as AI-based aging analysis of power transformer oil, AI in social media management, and AI-driven human detection systems. Further chapters address sentiment analysis, visual analysis for image processing, and the integration of AI in smart grid networks. The volume also covers AI applications in hardware security for wireless sensor networks, drone robotics, and crime prevention systems. The final set of chapters highlight AI’s role in healthcare and automation, including an AI-assisted system for women’s safety in India and the use of EfficientNet B0 CNN architecture for brain tumor detection and classification. Together, these chapters showcase the versatility and growing influence of AI and ML across critical modern industries. Key features A multidisciplinary approach covering AI applications in robotics, cybersecurity, healthcare, and digital transformation in 12 organized chapters. A focus on contemporary challenges and solutions in AI and ML across industries. Research-driven insights from experts and practitioners in the field. Practical discussions on AI-driven automation, security, and intelligent decision-making systems.