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Books in Artificial intelligence

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    • Federated Learning for the Metaverse

      • 1st Edition
      • January 11, 2026
      • Noor Zaman Jhanjhi + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 8 9 3 9
      • eBook
        9 7 8 0 4 4 3 3 3 8 9 4 6
      Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.

    • Connected Diagnoses

      • 1st Edition
      • March 1, 2026
      • Keshav Kaushik + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 8 2 9 9 4
      • eBook
        9 7 8 0 4 4 3 3 8 3 0 0 7
      Connected Diagnoses: IoT, Healthcare, and Digital Forensics investigates the complex intersection of IoT, healthcare, and digital forensics. This book explores the intricate relationships between these fields, with a focus on cybersecurity, patient data ethics, and challenges in IoT investigations. This book advances knowledge on leveraging IoT securely to enhance patient care and digital forensic analysis, providing significant insights from experts along with practical guidance for those operating at the crossroads of these critical disciplines. The book helps professionals grasp, adapt to, and capitalize on the interconnected nature of emerging technologies to ensure ethics, security, and safety. It is a comprehensive resource that benefits researchers and practitioners seeking to understand the convergence of medical technology, interconnected devices, and digital forensics.

    • Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

      • 1st Edition
      • March 1, 2026
      • Hanif Heidari + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 4 1 3 3 5
      • eBook
        9 7 8 0 4 4 3 3 4 1 3 4 2
      Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders discusses the latest developed methods in IoT and its applications in neurological disorders that emphasize end-user requirements. Intelligent IoT is used to explore the intersection between medicine, data science, biomedical engineering, and healthcare systems. A comprehensive overview of modelling and analyzing the requirements of people with neurological disorders is presented in this book. Signals and images of biological activity are collected and analyzed based on patient specifications to facilitate more accurate diagnosis and treatment. The book also discusses cutting-edge AI methods for IoT devices designed to treat neurological conditions.

    • AI and Data Science in Medical Research

      • 1st Edition
      • March 1, 2026
      • Olfa Boubaker
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 6 3 8 5
      • eBook
        9 7 8 0 4 4 3 2 7 6 3 9 2
      AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies.The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

    • Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics

      • 1st Edition
      • February 1, 2026
      • Sayooj Aby Jose + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 2 3 4 0
      • eBook
        9 7 8 0 4 4 3 3 3 2 3 5 7
      Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics offers a comprehensive exploration of innovative methodologies at the intersection of mathematics, biology, and medicine. This book delves into advanced mathematical modeling, artificial intelligence, and computational intelligence, providing essential tools for understanding and managing complex disease dynamics. Covering a wide range of topics, including fractional-order modeling, optimal control strategies, and privacy-preserving technologies, it addresses critical challenges in public health and healthcare systems. With contributions from leading experts, this volume bridges theoretical advancements and practical applications, making it an invaluable resource for researchers, healthcare professionals, and academics seeking interdisciplinary solutions to global health issues.

    • Transforming Industries, Empowering Societies

      • 1st Edition
      • January 12, 2026
      • Parikshit Narendra Mahalle + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 2 8 7 8 7
      • eBook
        9 7 8 0 4 4 3 3 2 8 7 9 4
      With the ever-increasing use of AI technologies, ethical considerations take on greater importance. Human-centric AI emphasizes transparency, making sure that AI systems work in a way that users can comprehend and trust. Additionally, it addresses bias and discrimination issues, ensuring fairness and inclusion in the design and implementation of AI apps. By emphasizing user experience, security, and human-centric AI, the goal is to improve collaboration between people and machines, rather than replacing human decisions, creating a future where technology is a force for good, benefiting both businesses and society. Written from a technological point of view, Industry 5.0 for Society 5.0 explores the impact of cutting-edge technologies, including the Internet of Things, cloud, artificial intelligence, and digital twin, on individuals and community, and considers how they can be used to solve societal problems. The book considers how these technologies can positively affect industry, healthcare, agriculture, design and manufacture, contributing to the development of a sustainable environment that ultimately creates a positive and mutually beneficial relationship between people and AI.

    • Autonomous Vehicle Safety Solutions

      • 1st Edition
      • January 1, 2026
      • Aparna Kumari
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 5 2 8 0
      • eBook
        9 7 8 0 4 4 3 3 3 5 2 9 7
      Autonomous Vehicle Safety Solutions: Foundations, Technologies, and Prospects for the Future addresses the dynamically evolving state of the art that traverses and brings together automotive engineering, electronics engineering, and computer science. Its technical overview of smart vehicles' capabilities, propelled by headway in artificial intelligence and sensor technologies, enables in-depth understanding of the safety-assurance complexities that guide their design and operation.The comprehensive volume distinguishes itself for its treatment of several exciting, emerging opportunities and trends, including machine learning algorithms, V2X connectivity, and cybersecurity. Up-to-date applications are featured through practical examples and expert insights, bringing additional value to a discourse which underscores the critical need for ongoing safety advancements and adaptability in the fast-moving context of autonomous driving systems, with their related implications on sustainability and society as a whole.The outcome is a cornerstone resource for academia and industry alike that encourages further transformative, interdisciplinary investigations to bring safety solutions to maturity and subsequent rigorous testing for validation standards to be defined, thus realizing, in a future not distant from now, a scenario where self-driving vehicles can co-exist seamlessly with traditional modes of transportation and also integrate reliably, efficiently, and without risks within the larger infrastructure.

    • Learning-Driven Game Theory for AI

      • 1st Edition
      • February 1, 2026
      • Mehdi Salimi + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 3 8 5 2 3
      • eBook
        9 7 8 0 4 4 3 4 3 8 5 3 0
      Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science. In this book, the authors bridge the gap between traditional game theory and its modern applications in artificial intelligence (AI) and related technological fields. The dynamic nature of contemporary problems in robotics, cybersecurity, machine learning, and multi-agent systems requires game-theoretic solutions that go beyond classical methods. The book delves into the rapidly growing intersection of pursuit differential games and AI, focusing on how these advanced game-theoretic models can be applied to modern AI systems, making it an indispensable resource for both academics and professionals. The book also provides a variety of applications demonstrating the practical integration of AI and game theory across various disciplines, such as autonomous systems, federated learning, and distributed decision-making frameworks. The book also explores the use of game theory in reinforcement learning, swarm intelligence, multi-agent coordination, and cybersecurity. These are critical areas where AI and dynamic games converge. Each chapter covers a different facet of dynamic games, offering readers a comprehensive yet focused exploration of topics such as differential and discrete-time games, evolutionary dynamics, and repeated and stochastic games. The absence of static games ensures a concentrated focus on the dynamic, evolving problems that are most relevant today.

    • Computational Intelligence in Surveillance Systems Using Image Processing

      • 1st Edition
      • February 1, 2026
      • Jay Kumar Pandey + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 4 0 8 2
      • eBook
        9 7 8 0 4 4 3 3 6 4 0 9 9
      Traditional surveillance systems struggle to process large volumes of visual data, identify specific objects or behaviors, and adapt to dynamic environments. Computational intelligence, which encompasses techniques like artificial intelligence (AI), machine learning (ML), and computer vision, offers powerful tools to address these challenges by enabling automated analysis, pattern recognition, and decision-making based on visual data. Computational Intelligence in Surveillance Systems Using Image Processing addresses the unique challenges and ethical considerations of applying AI and ML, offering a nuanced understanding of the regulatory landscape. It provides insights into the responsible development and deployment of technologies to unlock the transformative potential of computational intelligence to revolutionize surveillance systems and advance the capabilities of security and monitoring across various sectors.

Related subjects

Artificial intelligence expert systems and knowledge based systems

Artificial intelligence general

Cognitive science

Computer human interaction

Evolutionary computation genetic algorithms programming

Fuzzy logic

Machine learning

Natural language and computational linguistics

Neural networks

Planning and scheduling

Reasoning

Robotics and autonomous systems