Pankaj Bhambri – författare

Harnessing the Potential of Blockchain Technology in the Smart Healthcare explores a groundbreaking shift in how healthcare data are managed, shared, and secured. This book is an essential guide for anyone seeking a deep understanding of the intersection between blockchain and healthcare. It breaks down complex blockchain concepts and reveals their transformative impact on the industry.Across 27 insightful chapters, the readers will discover how blockchain can not only revolutionize electronic health records, strengthen data security and privacy, and streamline healthcare operations, but also empower patients with greater control over their health information.Through real-world case studies, expert insights, and practical strategies, the book equips healthcare professionals, technologists, and policymakers with the tools to leverage blockchain for a more efficient, transparent, and patient-centered healthcare system.By examining real-world applications and implementations, this book not only informs but also inspires action-paving the way for a future where healthcare is smarter, safer, and more equitable.Illuminates how blockchain technology enhances data security and privacy, assuaging concerns about patient information breachesExplores concrete strategies for interoperability, facilitating seamless data exchange among healthcare providers, and promoting a patient-centric approach to healthcareDelves into the complexities of regulatory compliance and suggests pathways for healthcare organizations to navigate the evolving regulatory landscape successfully

Today, relevant data are typically delivered to cloud-based servers for storing and analysis in order to extract key features and enable enhanced applications beyond the basic transmission of raw data and to realize the possibilities associated with the impending Internet of Things (IoT). To allow for quicker, more efficient, and expanded privacy-preserving services, a new trend called Fog Computing has emerged: moving these responsibilities to the network's edge.Traditional centralized cloud computing paradigms confront new problems posed by IoT application growth, including high latency, limited storage, and outages due to a lack of available resources. Fog Computing puts the cloud and IoT devices closer together to address these issues. Instead of sending IoT data to the cloud, the fog processes and stores it locally at IoT devices. Unlike the cloud, fog-based services have a faster reaction time and better quality overall. Fog Computing, Cloud Computing, and their connectivity with the IoT are discussed in this book, with an emphasis on the advantages and implementation issues. It also explores the various architectures and appropriate IoT applications. Fog Computing, Cloud Computing, and Internet of Things are being suggested as potential research directions.Features: A systematic overview of the state-of-the-art in Cloud Computing, Fog Computing, and Internet of ThingsRecent research results and some pointers to future advancements in architectures and methodologies Detailed examples from clinical studies using several different data sets

Today, relevant data are typically delivered to cloud-based servers for storing and analysis in order to extract key features and enable enhanced applications beyond the basic transmission of raw data and to realize the possibilities associated with the impending Internet of Things (IoT). To allow for quicker, more efficient, and expanded privacy-preserving services, a new trend called Fog Computing has emerged: moving these responsibilities to the network's edge.Traditional centralized cloud computing paradigms confront new problems posed by IoT application growth, including high latency, limited storage, and outages due to a lack of available resources. Fog Computing puts the cloud and IoT devices closer together to address these issues. Instead of sending IoT data to the cloud, the fog processes and stores it locally at IoT devices. Unlike the cloud, fog-based services have a faster reaction time and better quality overall. Fog Computing, Cloud Computing, and their connectivity with the IoT are discussed in this book, with an emphasis on the advantages and implementation issues. It also explores the various architectures and appropriate IoT applications. Fog Computing, Cloud Computing, and Internet of Things are being suggested as potential research directions.Features: A systematic overview of the state-of-the-art in Cloud Computing, Fog Computing, and Internet of ThingsRecent research results and some pointers to future advancements in architectures and methodologies Detailed examples from clinical studies using several different data sets

Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world's largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues.Features:Informs about cloud computing, IoT and big data, including theoretical foundations and the most recent empirical findingsProvides essential research on the relationship between various technologies and the aggregate influence they have on solving real-world problemsIdeal for academicians, developers, researchers, computer scientists, practitioners, information technology professionals, students, scholars, and engineers exploring research on the incorporation of technological innovations to address contemporary societal challenges

Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world's largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues.Features:Informs about cloud computing, IoT and big data, including theoretical foundations and the most recent empirical findingsProvides essential research on the relationship between various technologies and the aggregate influence they have on solving real-world problemsIdeal for academicians, developers, researchers, computer scientists, practitioners, information technology professionals, students, scholars, and engineers exploring research on the incorporation of technological innovations to address contemporary societal challenges

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments.The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency.A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments.The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency.A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.

This book presents the role of AI-Driven Digital Twin in the Industry 4.0 ecosystem by focusing on Smart Manufacturing, sustainable development, and many other applications. It also discusses different case studies and presents an in-depth understanding of the benefits and limitations of using AI and Digital Twin for industrial developments.AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications introduces the role of Digital Twin in Smart Manufacturing and focuses on the Digital Twin framework throughout. It provides a summary of the various AI applications in the Industry 4.0 environment and emphasizes the role of advanced computational and communication technologies. The book offers demonstrative examples of AI-Driven Digital Twin in various application domains and includes AI techniques used to analyze the environmental impact of industrial operations along with examples. The book reviews the major challenges in the deployment of AI-Driven Digital Twin in the Industry 4.0 ecosystem and presents an understanding of how AI is used in the designing of Digital Twin for various applications. The book also enables familiarity with various industrial applications of computational and communication technologies and summarizes the ongoing research and innovations in the areas of AI, Digital Twin, and Smart Manufacturing while also tracking the various research challenges along with future advances.This reference book is a must-read and is very beneficial to students, researchers, academicians, industry experts, and professionals working in related fields.

This book presents the role of AI-Driven Digital Twin in the Industry 4.0 ecosystem by focusing on Smart Manufacturing, sustainable development, and many other applications. It also discusses different case studies and presents an in-depth understanding of the benefits and limitations of using AI and Digital Twin for industrial developments.AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications introduces the role of Digital Twin in Smart Manufacturing and focuses on the Digital Twin framework throughout. It provides a summary of the various AI applications in the Industry 4.0 environment and emphasizes the role of advanced computational and communication technologies. The book offers demonstrative examples of AI-Driven Digital Twin in various application domains and includes AI techniques used to analyze the environmental impact of industrial operations along with examples. The book reviews the major challenges in the deployment of AI-Driven Digital Twin in the Industry 4.0 ecosystem and presents an understanding of how AI is used in the designing of Digital Twin for various applications. The book also enables familiarity with various industrial applications of computational and communication technologies and summarizes the ongoing research and innovations in the areas of AI, Digital Twin, and Smart Manufacturing while also tracking the various research challenges along with future advances.This reference book is a must-read and is very beneficial to students, researchers, academicians, industry experts, and professionals working in related fields.

Advancements in computational intelligence, which encompasses artificial intelligence, machine learning, and data analytics, have revolutionized the way we process and analyze biomedical and health data. These techniques offer novel approaches to understanding complex biological systems, improving disease diagnosis, optimizing treatment plans, and enhancing patient outcomes. Computational Intelligence and Blockchain in Biomedical and Health Informatics introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields and provides a framework and summary of the various methods. The book emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. Techniques to analyze the impacts on the biomedical and health Informatics domains are discussed along with major challenges in deployment. Rounding out the book are highlights of the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability along with two case studies. This book is highly beneficial to educators, researchers, and anyone involved with health data.Features:• Introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields.• Provides a framework and a summary of various computational intelligence and blockchain methods.• Emphasizes the role of advanced computational techniques and offers demonstrative examples throughout.• Techniques to analyze the impact on biomedical and health informatics are discussed along with major challenges in deployment.• Highlights the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability.

Advancements in computational intelligence, which encompasses artificial intelligence, machine learning, and data analytics, have revolutionized the way we process and analyze biomedical and health data. These techniques offer novel approaches to understanding complex biological systems, improving disease diagnosis, optimizing treatment plans, and enhancing patient outcomes. Computational Intelligence and Blockchain in Biomedical and Health Informatics introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields and provides a framework and summary of the various methods. The book emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. Techniques to analyze the impacts on the biomedical and health Informatics domains are discussed along with major challenges in deployment. Rounding out the book are highlights of the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability along with two case studies. This book is highly beneficial to educators, researchers, and anyone involved with health data.Features:• Introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields.• Provides a framework and a summary of various computational intelligence and blockchain methods.• Emphasizes the role of advanced computational techniques and offers demonstrative examples throughout.• Techniques to analyze the impact on biomedical and health informatics are discussed along with major challenges in deployment.• Highlights the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability.

Blockchain and distributed-ledger technologies enable new modes of communication, synchronization, and transfer of value with a broad impact on Internet of Things (IoT), Data Science, society, industry, commerce, and government. This book studies the potential impact of blockchain and distributed-ledger technologies on IoT. It highlights the application of possible solutions in the domain of blockchain and IoT system security, including cryptology, distributed systems, law, formal methods, code verification and validation, software, and systems metrics. As the field is growing fast, the book adapts to the changing research landscape, integrates and cross-links studies and citations in related subfields, and provides an overview of these fields and how they complement each other.• Highlights how the security aspect of the integration of blockchain with IoT will help to design secure data solutions for various domains• Offers fundamental knowledge of the blockchain concept and its usage in real-life applications• Presents current and future trends on the IoT and blockchain with an efficient, scalable, and sustainable approach• Reviews future developments in blockchain and IoT in future job opportunities• Discusses how blockchain for IoT systems can help a varied range of end-users to access computational and storage resourcesThis book is intended for postgraduate students and researchers in the departments of computer science, working in the areas of IoT, blockchain, deep learning, machine learning, image processing, and big data.

Blockchain and distributed-ledger technologies enable new modes of communication, synchronization, and transfer of value with a broad impact on Internet of Things (IoT), Data Science, society, industry, commerce, and government. This book studies the potential impact of blockchain and distributed-ledger technologies on IoT. It highlights the application of possible solutions in the domain of blockchain and IoT system security, including cryptology, distributed systems, law, formal methods, code verification and validation, software, and systems metrics. As the field is growing fast, the book adapts to the changing research landscape, integrates and cross-links studies and citations in related subfields, and provides an overview of these fields and how they complement each other.• Highlights how the security aspect of the integration of blockchain with IoT will help to design secure data solutions for various domains• Offers fundamental knowledge of the blockchain concept and its usage in real-life applications• Presents current and future trends on the IoT and blockchain with an efficient, scalable, and sustainable approach• Reviews future developments in blockchain and IoT in future job opportunities• Discusses how blockchain for IoT systems can help a varied range of end-users to access computational and storage resourcesThis book is intended for postgraduate students and researchers in the departments of computer science, working in the areas of IoT, blockchain, deep learning, machine learning, image processing, and big data.

Recently, the fields of Artificial Intelligence (AI) and the Internet of Things (IoT) have revolutionized numerous industries, including healthcare. The convergence of AI and IoT has given birth to smart healthcare systems, transforming the way we deliver, receive, and experience healthcare services. This book explores the profound impact of these technologies on healthcare and presents a comprehensive overview of their applications, challenges, and prospects.Smart Healthcare Systems: AI and IoT Perspectives addresses various aspects of how smart healthcare can be used to detect and analyze diseases, the underlying methodologies, and related security concerns. It also discusses healthcare as a multidisciplinary field that involves a range of sectors such as the financial system, social factors, health technologies, and organizational structures that affect individuals, families, institutions, organizations, and populations’ healthcare. The book presents the goals of healthcare services which include patient safety, timeliness, effectiveness, efficiency, and equity. An outline of what smart healthcare consists of which is m-health, e-health, electronic resource management, smart and intelligent home services, and medical devices is included. Along with highlights on how AI and IoT-enabled healthcare technologies are suitable for remote health monitoring, including rehabilitation, and assisted ambient living. Rounding the offers of this book out is that it also covers how healthcare analytics can be applied to the data gathered from different areas to improve healthcare at a minimum expense.Researchers, Academicians, Industry, R&D Organizations, medical professionals, PG students, and policymakers in the fields of artificial intelligence, the internet of things, healthcare informatics, biomedical engineering, medical informatics, and related subjects can use this book to assist them in making appropriate decisions regarding these emerging disciplines.

Recently, the fields of Artificial Intelligence (AI) and the Internet of Things (IoT) have revolutionized numerous industries, including healthcare. The convergence of AI and IoT has given birth to smart healthcare systems, transforming the way we deliver, receive, and experience healthcare services. This book explores the profound impact of these technologies on healthcare and presents a comprehensive overview of their applications, challenges, and prospects.Smart Healthcare Systems: AI and IoT Perspectives addresses various aspects of how smart healthcare can be used to detect and analyze diseases, the underlying methodologies, and related security concerns. It also discusses healthcare as a multidisciplinary field that involves a range of sectors such as the financial system, social factors, health technologies, and organizational structures that affect individuals, families, institutions, organizations, and populations’ healthcare. The book presents the goals of healthcare services which include patient safety, timeliness, effectiveness, efficiency, and equity. An outline of what smart healthcare consists of which is m-health, e-health, electronic resource management, smart and intelligent home services, and medical devices is included. Along with highlights on how AI and IoT-enabled healthcare technologies are suitable for remote health monitoring, including rehabilitation, and assisted ambient living. Rounding the offers of this book out is that it also covers how healthcare analytics can be applied to the data gathered from different areas to improve healthcare at a minimum expense.Researchers, Academicians, Industry, R&D Organizations, medical professionals, PG students, and policymakers in the fields of artificial intelligence, the internet of things, healthcare informatics, biomedical engineering, medical informatics, and related subjects can use this book to assist them in making appropriate decisions regarding these emerging disciplines.

In the context of an ever-changing technological world, it is crucial to prioritize the cultivation of sustainability and environmental consciousness. Adopting an interdisciplinary perspective, this handbook facilitates the integration of technology and sustainability by leveraging insights from many fields such as engineering, environmental science, economics, and sociology. The primary objective of this handbook is to provide a comprehensive analysis of the complex relationship between technology and the environment.Handbook of Technological Sustainability: Innovation and Environmental Awareness includes recent and diverse case studies from a global perspective and demonstrates the utilization of technology to achieve sustainable development across several sectors, such as energy, agriculture, transportation, and urban planning. It explores innovative technologies emphasizing state-of-the-art and developing technologies, including renewable energy, circular economy practices, smart cities, and artificial intelligence-driven sustainability solutions. The handbook also examines the impact of laws, regulations, and international agreements on the advancement or impediment of technological sustainability. Written to be used as a reference, this handbook highlights the ethical and moral quandaries linked to technological sustainability analyzing various topics of significance, including environmental justice, privacy implications in smart technology, and the ramifications of artificial intelligence on employment and society. It provides practical methodologies and recommendations for individuals, enterprises, and governmental entities to adopt and integrate sustainable technologies effectively and furnish readers with a comprehensive guide for transitioning towards a more sustainable future.As it showcases perspectives from technologists, sustainability professionals, and policymakers that have the potential to provide a range of opinions and practical insights derived from real-world experiences, this handbook is a book for all individuals, corporations, governments, researchers, and anyone seeking to harness technology to advance sustainability and effectively tackle the multifaceted issues posed by our dynamic global landscape.

In the context of an ever-changing technological world, it is crucial to prioritize the cultivation of sustainability and environmental consciousness. Adopting an interdisciplinary perspective, this handbook facilitates the integration of technology and sustainability by leveraging insights from many fields such as engineering, environmental science, economics, and sociology. The primary objective of this handbook is to provide a comprehensive analysis of the complex relationship between technology and the environment.Handbook of Technological Sustainability: Innovation and Environmental Awareness includes recent and diverse case studies from a global perspective and demonstrates the utilization of technology to achieve sustainable development across several sectors, such as energy, agriculture, transportation, and urban planning. It explores innovative technologies emphasizing state-of-the-art and developing technologies, including renewable energy, circular economy practices, smart cities, and artificial intelligence-driven sustainability solutions. The handbook also examines the impact of laws, regulations, and international agreements on the advancement or impediment of technological sustainability. Written to be used as a reference, this handbook highlights the ethical and moral quandaries linked to technological sustainability analyzing various topics of significance, including environmental justice, privacy implications in smart technology, and the ramifications of artificial intelligence on employment and society. It provides practical methodologies and recommendations for individuals, enterprises, and governmental entities to adopt and integrate sustainable technologies effectively and furnish readers with a comprehensive guide for transitioning towards a more sustainable future.As it showcases perspectives from technologists, sustainability professionals, and policymakers that have the potential to provide a range of opinions and practical insights derived from real-world experiences, this handbook is a book for all individuals, corporations, governments, researchers, and anyone seeking to harness technology to advance sustainability and effectively tackle the multifaceted issues posed by our dynamic global landscape.

Digital Sustainability: Navigating Entrepreneurship in the Information Age explores the intersection of technology and sustainability, offering a panoramic view of innovative strategies and solutions for building a more environmentally conscious and socially responsible future. From exploring the transformative potential of blockchain technology in sustainable supply chains to harnessing the power of Artificial Intelligence (AI) and machine learning for environmental monitoring and conservation, each chapter presents cutting-edge insights and practical applications. The book highlights the ethical implications of entrepreneurship and data privacy, focusing on the potential of AI and machine learning for sustainable resource utilization and decision-making processes. Delving into areas such as renewable energy integration, data privacy, cybersecurity, IoT entrepreneurship, smart cities, and beyond, this book equips entrepreneurs, policymakers, and researchers with the knowledge and tools needed to drive meaningful change in the digital era. With a rich tapestry of case studies, future perspectives, and actionable insights, this book offers a roadmap for entrepreneurs, engineers, business professionals, and those interested in technology and sustainability, focusing on redefining business models, fostering innovation, and creating a more connected, sustainable world.

Digital Sustainability: Navigating Entrepreneurship in the Information Age explores the intersection of technology and sustainability, offering a panoramic view of innovative strategies and solutions for building a more environmentally conscious and socially responsible future. From exploring the transformative potential of blockchain technology in sustainable supply chains to harnessing the power of Artificial Intelligence (AI) and machine learning for environmental monitoring and conservation, each chapter presents cutting-edge insights and practical applications. The book highlights the ethical implications of entrepreneurship and data privacy, focusing on the potential of AI and machine learning for sustainable resource utilization and decision-making processes. Delving into areas such as renewable energy integration, data privacy, cybersecurity, IoT entrepreneurship, smart cities, and beyond, this book equips entrepreneurs, policymakers, and researchers with the knowledge and tools needed to drive meaningful change in the digital era. With a rich tapestry of case studies, future perspectives, and actionable insights, this book offers a roadmap for entrepreneurs, engineers, business professionals, and those interested in technology and sustainability, focusing on redefining business models, fostering innovation, and creating a more connected, sustainable world.

In today’s digital age, the risks to data and infrastructure have increased in both range and complexity. As a result, companies need to adopt cutting-edge artificial intelligence (AI) solutions to effectively detect and counter potential threats. This handbook fills the existing knowledge gap by bringing together a team of experts to discuss the latest advancements in security systems powered by AI. The handbook offers valuable insights on proactive strategies, threat mitigation techniques, and comprehensive tactics for safeguarding sensitive data.Handbook of AI-Driven Threat Detection and Prevention: A Holistic Approach to Security explores AI-driven threat detection and prevention, and covers a wide array of topics such as machine learning algorithms, deep learning, natural language processing, and so on. The holistic view offers a deep understanding of the subject matter as it brings together insights and contributions from experts from around the world and various disciplines including computer science, cybersecurity, data science, and ethics. This comprehensive resource provides a well-rounded perspective on the topic and includes real-world applications of AI in threat detection and prevention emphasized through case studies and practical examples that showcase how AI technologies are currently being utilized to enhance security measures. Ethical considerations in AI-driven security are highlighted, addressing important questions related to privacy, bias, and the responsible use of AI in a security context. The investigation of emerging trends and future possibilities in AI-driven security offers insights into the potential impact of technologies like quantum computing and blockchain on threat detection and prevention.This handbook serves as a valuable resource for security professionals, researchers, policymakers, and individuals interested in understanding the intersection of AI and security. It equips readers with the knowledge and expertise to navigate the complex world of AI-driven threat detection and prevention. This is accomplished by synthesizing current research, insights, and real-world experiences.

Cloud computing has revolutionized digital infrastructure, but it has also introduced complex forensic challenges that demand intelligent, scalable, and automated investigative solutions. AI Driven Cloud Forensics: Advanced Techniques for Next Generation Digital Investigations provides a comprehensive exploration of how artificial intelligence, machine learning, big data analytics, and automation are transforming the future of digital forensics in cloud environments. This edited volume examines advanced methodologies for forensic acquisition in virtual machines, containers, and ephemeral environments; intelligent cloud architectures for secure investigations; and AI-powered frameworks for anomaly detection, fraud investigation, phishing detection, and log analysis. It highlights emerging approaches such as AutoML-enabled forensic systems, federated learning for communication-efficient anomaly detection, AI-centric privileged access management, and real-time detection of data fabrication attacks in decentralized systems. Beyond core forensic technologies, the book addresses interdisciplinary applications across smart micro-grids, dark web environments, digital supply chains, tourism systems, and e-discovery processes. By integrating automation with forensic intelligence, the contributors demonstrate how next-generation digital investigations can become more proactive, predictive, and adaptive. Special emphasis is placed on addressing challenges such as data volatility, multi-tenancy, encryption, jurisdictional constraints, and large-scale log analysis in distributed cloud ecosystems. The book also includes a bibliometric and science-mapping analysis to provide insights into evolving research trends in AI-driven cloud forensic automation. Designed for researchers, cybersecurity professionals, forensic analysts, legal practitioners, cloud architects, and postgraduate students, this volume bridges theoretical foundations with real-world implementations. It serves as a forward-looking reference for building resilient, trustworthy, and AI-enabled forensic ecosystems capable of responding to increasingly sophisticated cyber threats. By combining innovation with investigative rigor, AI Driven Cloud Forensics contributes to shaping the next generation of intelligent digital security and forensic readiness in cloud-driven environments.

Master the shift from centralized clouds to the network’s edge with this essential guide, providing real-world case studies and 6G strategies to build faster, more reliable industrial systems. 6G, the next generation of wireless communication technology, will enable unparalleled connectivity and data transfer speeds with ultra-reliable, low-latency transmission. This means better processing and decision-making in real-time. Instead of storing and processing the user’s data in a centralized cloud, edge intelligence allows users to process data locally, at the network’s periphery. With 6G-enabled IIoT, data from industrial devices and sensors can be handled locally, resulting in lower latency and faster response times for mission-critical applications. This book introduces edge intelligence and the 6G-enabled industrial Internet of Things ecosystem. It offers practical guidance and fosters a deeper understanding of how edge intelligence can be integrated with 6G-enabled IIoT applications and frameworks in a modern industrial environment. Through case studies and real-life examples, it will explore the complexities associated with real-life implementations for industrial applications, making it an invaluable resource in today’s digitally industrial ecosystem. Readers will find the volume: Provides a clear overview of edge intelligence and 6G-enabled IIoT integration;Bridges the gap between theoretical concepts and real-life industrial use cases;Includes real-world case studies to illustrate practical applications;Offers strategies to overcome industrial implementation challenges.Audience Engineers, data scientists, researchers, and technology professionals who are involved in industrial IoT, edge computing, and emerging 6G technologies.

In an era defined by global disruptions, sustainability mandates and rapid technological advancement, Next-Gen Supply Chains provides an essential roadmap for navigating the complex transformation of global supply networks. This comprehensive book moves beyond isolated trends to present an integrated framework where generative AI, blockchain, autonomous systems and the Internet of Things converge to build resilient, efficient and responsible operations.This book masterfully bridges the critical gap between theoretical concepts and practical implementation, offering readers actionable strategies, detailed case studies from industry leaders such as Amazon and Lenovo, and robust frameworks for risk management, ethical AI governance and circular economy integration. With its unique emphasis on the synergy between technological innovation and the necessary human capital development, the book is an indispensable resource for supply chain executives, operations managers, technology implementers and academics seeking to future-proof their organizations and master the strategic imperatives of the modern supply chain landscape.