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Elsevier

Books in Artificial intelligence expert systems and knowledge based systems

  • Healthcare 5.0

    Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data
    • 1st Edition
    • Yugal Kumar + 2 more
    • English
    Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data addresses the urgent need for innovation in today’s complex healthcare data landscape that is characterized by pandemics, aging populations, and chronic conditions. The book introduces the concept of ‘Healthcare 5.0’ as an interconnected, data-driven, and patient-centric framework where advanced technologies such as AI, ML, IoMT, Big Data, and Large Language Models (LLMs) converge to optimize care, streamline operations, and deliver personalized, predictive solutions. The book moves from core AI applications in electronic health records, drug discovery, data management, and privacy, through cutting-edge big data analytics for disease forecasting and diagnosis.It explores new research advances in the Internet of Medical Things, including connected device architectures and their fusion with AI for dynamic decision-making. The third section focuses on data analytics in telemedicine, remote care, system usability, and integration in Healthcare 5.0. The personalized healthcare section details analysis and applications in AI- and IoT-powered assistance, and real-time monitoring. The last section explores the development of LLMs and their applications in medical imaging, clinical decision support, predictive analytics, system architectures, as well as the ethical challenges of their deployment in healthcare.

  • Artificial Intelligence and Machine Learning for Safety-Critical Systems

    A Comprehensive Guide
    • 1st Edition
    • Rajiv Pandey + 3 more
    • English
    Artificial Intelligence and Machine Learning for Safety-Critical Systems: A Comprehensive Guide provides engineers and system designers who are exploring the application of AI/ML methods for safety-critical systems with a dedicated resource on the challenges and mitigation strategies involved in their design. The book's authors present ML techniques in safety-critical systems across multiple domains, including pattern recognition, image processing, edge computing, Internet of Things (IoT), encryption, hardware accelerators, and many others. These applications help readers understand the many challenges that need to be addressed in order to increase the deployment of ML models in critical systems. In addition, the book shows how to improve public trust in ML systems by providing explainable model outputs rather than treating the system as a black box for which the outputs are difficult to explain. Finally, the authors demonstrate how to meet legal certification and regulatory requirements for the appropriate ML models. In essence, the goal of this book is to help ensure that AI-based critical systems better utilize resources, avoid failures, and increase system safety and public safety.

  • System of Systems Engineering

    Innovations, Challenges, and Future Directions
    • 1st Edition
    • Bedir Tekinerdogan + 1 more
    • English
    System of Systems Engineering: Innovations, Challenges, and Future Directions focuses on the many aspects of System of Systems Engineering. Part I, Foundations of System of Systems Engineering, introduces the field, characterizes and classifies SoS, and discusses key concepts. Part II, Governance and Management of SoSE, covers strategic governance, policy and regulatory frameworks, and leadership and decision-making in SoSE projects. Part III, Methodologies and Tools, explores systems thinking and modeling approaches, lifecycle management, and interoperability and integration strategies. Part IV, AI and System of Systems Engineering, delves into leveraging AI for enhanced decision-making, machine learning applications, AI-driven automation and control, and ethical considerations.Final... Part V, Case Studies and Emerging Challenges, presents real-world applications in defense and aerospace, smart cities, healthcare, environmental and energy systems, and discusses future directions and research opportunities. This book offers significant benefits to graduate students, researchers, and professionals in software engineering, systems engineering, aerospace engineering, defense, telecommunications, and other fields where SoSE is relevant.

  • Computational Intelligence in Mechatronics

    Solving Real-World Problems in Electronic Systems Design
    • 1st Edition
    • Mohamed Arezki Mellal
    • English
    Computational Intelligence in Mechatronics: Solving Real-World Problems in Electronic Systems Design provides a comprehensive exploration of the diverse applications of computational intelligence in the realm of applied electronics. By compiling cutting-edge research and practical case studies, the book bridges the gap between theory and practice, offering insights into how CI techniques can be effectively utilized to solve real-world problems in electronic systems design, analysis, and optimization. Through a combination of theoretical foundations, algorithmic implementations, and practical examples, readers will gain a deeper understanding of the potential benefits and limitations of CI in various applications within the field of applied electronics.From optimizing circuit designs to enhancing signal processing algorithms, CI has demonstrated its efficacy in addressing challenges across diverse domains such as telecommunications, consumer electronics, renewable energy systems, and medical devices. As the demand for intelligent electronic systems continues to grow, understanding and harnessing the potential of computational intelligence becomes imperative for researchers, engineers, and practitioners in the field of applied electronics.

  • Green Intrusion Detection Systems for IoT

    • 1st Edition
    • Saeid Jamshidi + 3 more
    • English
    Green Intrusion Detection Systems for IoT tackles the pressing security challenges posed by the rapid expansion of the Internet of Things (IoT). The book delves into innovative, lightweight security models and energy-aware IDS mechanisms that strike a balance between security efficacy, computational efficiency, and environmental sustainability. Sections discuss the transformative role of IoT and the need for sustainable security solutions, highlight the distinctions between traditional and Green IDS, focus on lightweight security models essential for resource-constrained IoT devices, and delve into energy-efficient network designs.Additional sections explore green IDS mechanisms, including machine learning and distributed approaches, IoT vulnerabilities and mitigation strategies, practical examples of sustainable IDS in various smart environments, real-world case studies, and future directions in sustainable IoT security. The book concludes with actionable recommendations that align technological advancements with global sustainability goals.

  • Smart Healthcare 2.0

    Integrating Digital Twins with AI-Driven Predictive Analytics
    • 1st Edition
    • Ramesh Chandra Poonia + 1 more
    • English
    Smart Healthcare 2.0: Integrating Digital Twins with AI-Driven Predictive Analytics offers a groundbreaking exploration of how digital twin technology, combined with real-time sensing and predictive analytics, is transforming healthcare delivery. As the global healthcare landscape shifts toward proactive, personalized care, this book addresses the urgent need for comprehensive resources that unify artificial intelligence, Internet of Things (IoT), and biomedical engineering within the digital twin framework. It provides an essential guide for researchers, engineers, and clinicians aiming to harness virtual patient models and data-driven insights to improve health outcomes and system efficiency in the era of ubiquitous healthcare.This volume covers a wide spectrum of topics, starting with foundational concepts of digital twins in precision health and advancing through smart sensing technologies, scalable system architectures, and AI-powered predictive analytics. Readers will explore detailed discussions on edge-cloud computing, secure communication protocols including blockchain, and simulation platforms that enable virtual patient modeling. The book also addresses critical themes such as chronic disease management, emergency response optimization, ethical AI deployment, interoperability standards, and workforce readiness. Real-world case studies and future-focused chapters on cognitive twins and quantum simulation provide a rich, multidisciplinary perspective.

  • Digital Twins

    Core Principles and AI Integration
    • 1st Edition
    • Bedir Tekinerdogan + 1 more
    • English
    Digital Twins: Core Principles and AI Integration offers a structured and up-to-date overview of digital twin technology, combining foundational principles with the rapidly growing role of artificial intelligence (AI). This book introduces the core concepts, modeling approaches, and software and systems engineering foundations needed to design and implement digital twins effectively. It then explores architectural methods, lifecycle management, interoperability, and the alignment between physical systems and their digital representations. A central part of this book focuses on data science and AI-enabled digital twins, demonstrating how machine learning, deep learning, generative AI, and autonomous agents enhance predictive analytics, optimization, anomaly detection, and automated decision-making. Integration with Internet of Things (IoT), cloud–edge infrastructures, big data analytics, and XR technologies further shows how intelligent digital twins evolve into adaptive and interactive systems. Real-world applications from manufacturing, agriculture, food systems, energy, mobility, healthcare, and urban environments illustrate the practical value of AI-driven digital twins. This book concludes with key challenges and future directions, including trustworthy AI, security, data governance, and the scaling of digital twin ecosystems.

  • AI Platforms as Global Governance for the Health Ecosystem

    The Future's Global Hospital
    • 1st Edition
    • Dominique J. Monlezun
    • English
    AI Platforms as Global Governance for the Health Ecosystem: The Future’s Global Hospital provides comprehensive and actionable approaches for readers to understand and optimize responsible AI to create global governance for the healthcare ecosystem. The book explores how AI platforms can transform hospitals and clinical practice by digitally unifying patients, providers, and payors, advancing healthcare for all. Users will find content that defines and explains the main hurdles and technical innovations in responsibly governing AI platforms for efficient, equitable, and sustainable global healthcare.Additiona... sections delve into the history, science, politics, economics, ethics, policy, and future of these AI platforms, and how governance efforts can work toward the common good. Written from the first-hand perspective of a practicing physician-data scientist and AI ethicist, the book maps out how to develop successful governance for AI platforms.

  • Metaverse and AI in Healthcare

    A Federated Learning Approach
    • 1st Edition
    • Jyotir Moy Chatterjee + 1 more
    • English
    Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. The book fills a critical gap by exploring how federated learning enables secure, decentralized data sharing and personalized medicine in virtual health platforms, meeting urgent demands for privacy, interoperability, and innovation. The book is structured into four parts covering foundational AI and federated learning concepts, augmented reality and metaverse applications, legal and cybersecurity challenges, and emerging strategic trends.Contributors from academia and industry present chapters on predictive modeling, cybersecurity frameworks, AR fitness, legal perspectives, and AI-driven medical tourism which are supported by case studies and technical explanations. This reference equips graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare with practical knowledge and forward-looking analysis.

  • Digital Transformation in Artificial Systems

    Engineering Requirements and Political, Economic, and Philosophical Challenges
    • 1st Edition
    • Mirko Farina + 3 more
    • English
    The last decade has seen exponential growth in the development of digital technologies. This has led to significant shifts in the political arena as well as in the economy, precipitating a series of revolutionary changes in the fabric of our societies, which have had far-reaching consequences and effects on the way we relate and connect to each other. Digital Transformation in Artificial Systems: Engineering Requirements and Political, Economic, and Philosophical Challenges focuses on analyzing the engineering requirements as well as the political consequences, overarching the philosophical and ethical implications of this transformation, especially in relation to its application in artificial systems. In this context, the concept of digital transformation (understood as the practice of redefining models, functions, operations, processes, and activities by leveraging technological advancements to build efficient digital environments) has become increasingly important. This book brings together key concepts, ideas, and frameworks related to this idea. It promotes an inclusive and responsible digital transformation capable of addressing the constraints on the global digital divide, deepening cooperation in digitization, industrialization, and innovation, while furthering our understanding of the ethical and moral challenges associated with such a development. The distinctive and most original element of the book is its interdisciplinarity. It will allow readers to gather crucial insights that will be instrumental to better understand the reach of the forthcoming AI revolution, its multidimensionality, and its potential impact on people and society.