Books in Artificial intelligence

Robotics for Intervention in Healthcare

1st Edition
January 1, 2026
Françoise J Siepel
English

Robotics for Intervention in Healthcare: From Technology to Clinical Practice bridges the gap between deep-core robotic intervention technology and clinical aspects including the physicians and the clinicians working and gives insight in the importance of connectivity at early stage but especially address which aspects are important to speed up the innovation chain.

Cybersecurity for Healthcare Systems in the Internet of Medical Things Era

1st Edition
January 1, 2026
Janmenjoy Nayak + 2 more
English

Cybersecurity for Healthcare Systems in the Internet of Medical Things Era is driven by the imperative to address the intricate convergence of healthcare, technology, and security. In response to the burgeoning challenges presented by the Internet of Medical Things (IoMT), this book is designed to be an indispensable resource for computer systems experts, healthcare staff, and executives. It goes beyond the surface, offering strategic insights and actionable strategies that encompass not only the IoMT landscape but also the intersection of artificial intelligence, signal processing, and cyber security. Cybersecurity for Healthcare Systems in the IoMT Era serves as a problem-solving compass for a diverse readership in the healthcare landscape. For healthcare professionals and IT leaders, the book untangles the complexities of integrating and securing Internet of Medical Things (IoMT) devices, offering a roadmap for understanding and navigating this rapidly evolving terrain. Biomedical engineers, burdened with strategic and everyday decisions, find in this book strategic insights and actionable strategies, empowering them to make informed choices amidst the ever-changing challenges posed by technology and cybersecurity threats. The authors present a comprehensive guide that not only elucidates the challenges and opportunities presented by IoMT but also explores how the synergy of AI and signal processing can elevate healthcare systems. This integration is crucial in deciphering the intricate nuances of medical data, enhancing diagnostics, and fortifying the security of interconnected healthcare networks.

Industry 4.0 and Sustainability

1st Edition
January 1, 2026
Muhammad Imran Khan + 2 more
English

The Fourth Industrial Revolution, commonly termed Industry 4.0, is transforming production and manufacturing through integration of advanced digital technologies like artificial intelligence (AI), industrial internet of things (IIoT), big data analytics, additive manufacturing, and advanced robotics. While much discussion has centered on potential economic impacts, Industry 4.0 also holds significant implications for sustainability across environmental, social, and economic dimensions. However, simply adopting technologies does not guarantee sustainability benefits, and improperly managed, they pose risks related to job losses, inequality, and rebound effects that must be addressed through integrative frameworks. ‘Industry 4.0 and Sustainability’ will provide the first comprehensive, evidence-based perspective unifying technological, organizational, policy, and social considerations to strategically direct Industry 4.0 innovations towards improved sustainability across economic, environmental, and social dimensions. With applied case studies and integrated roadmaps spanning engineering, management, and policy, it fills a crucial gap in guiding Industry 4.0 deployments to accelerate progress on sustainable development goals.

Multilevel Quantum Metaheuristics

1st Edition
January 1, 2026
Siddhartha Bhattacharyya + 4 more
English

Multilevel Quantum Metaheuristics: Applications in Data Exploration explores the most recent advances in hybrid quantum-inspired algorithms. Combining principles of quantum mechanics with metaheuristic techniques for efficient data optimization, this book examines multilevel quantum systems characterized by qudits and higher-level quantum states as more robust alternatives to conventional bilevel quantum approaches. It introduces novel multilevel applications of quantum metaheuristics for addressing optimization problems in areas including function optimization, data analysis, scheduling, and signal processing. The book also showcases real-world examples, case studies, and contributions that emphasize the effectiveness of proposed multilevel techniques over existing bilevel methods. Researchers, professionals, and engineers working on intelligent computing, quantum computing, data processing, clustering, and analysis, and those interested in the synergies between quantum computing, metaheuristics, and multilevel quantum systems for enhanced data exploration and analysis will find this book to be of great value.

Autonomous Vehicle Safety Solutions

1st Edition
January 1, 2026
Aparna Kumari
English

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.

Challenges and Applications of Generative Large Language Models

1st Edition
January 1, 2026
Anitha S. Pillai + 2 more
English

Large Language Models (LLMs) are a form of generative AI, based on Deep Learning, that rely on very large textual datasets, and are composed of hundreds of millions (or even billions) of parameters. LLMs can be trained and then refined to perform several NLP tasks like generation of text, summarization, translation, prediction, and more. Challenges and Applications of Generative Large Language Models assists readers in understanding LLMs, their applications in various sectors, challenges that need to be encountered while developing them, open issues, and ethical concerns. LLMs are just one approach in the huge set of methodologies provided by AI. The book, describing strengths and weaknesses of such models, enables researchers and software developers to decide whether an LLM is the right choice for the problem they are trying to solve. AI is the new buzzword, in particular Generative AI for human language (LLMs). As such, an overwhelming amount of hype is obfuscating and giving a distorted view about AI in general, and LLMs in particular. Thus, trying to provide an objective description of LLMs is useful to any person (researcher, professional, student) who is starting to work with human language. The risk, otherwise, is to forget the whole set of methodologies developed by AI in the last decades, sticking with only one model which, although very powerful, has known weaknesses and risks. Given the high level of hype around such models, Challenges and Applications of Generative Large Language Models (LLMs) enables readers to clarify and understand their scope and limitations.

Harnessing Artificial Intelligence to Ensure Diverse Global Teams

1st Edition
January 1, 2026
Harish Garg + 3 more
English

Harnessing Artificial Intelligence to Ensure Diverse Global Teams explores new research and applications of AI which can be used to address the distinct challenges of diverse, distributed teams. Incorporating compelling case studies and strategic guidance, the book demonstrates how AI can be developed and applied within systems and programs to promote inclusion, break down barriers, and enhance collaboration in cross-cultural organizational settings. Providing case studies and examples, this book equips computer scientists and engineers with actionable strategies for integrating AI seamlessly into programs and applications designed for diverse global teams. With contributions from experts in AI and team dynamics, this book will benefit leaders and team members seeking to leverage AI for improved teamwork across geographical and cultural boundaries, providing an up-to-date resource for uniting, uplifting, and optimizing global collaborations through inclusive artificial intelligence.

Edge Intelligence

1st Edition
January 1, 2026
Jawad Ahmad + 5 more
English

Edge Intelligence: Advanced Deep Transfer Learning for IoT Security presents a comprehensive exploration into the critical intersection of cybersecurity, edge computing, and deep learning, offering practitioners, researchers, and cybersecurity professionals a definitive guide to protect IoT/IIoT systems. This book delves into the synergistic potential of edge computing and advanced machine/deep learning algorithms, providing insights into lightweight and resource-efficient models with a special focus on resource-constrained edge devices. The rapidly evolving nature of cyberattacks underscores the need for updated and integrated resources that address the intersection of cybersecurity, edge computing, and deep learning. The authors address this issue by offering practical insights, lightweight models, and proactive defense mechanisms tailored to the unique challenges of securing edge devices and networks. This book is not only written to provide its audience effective strategies to detect and mitigate network intrusions by leveraging edge intelligence and advanced deep transfer learning techniques but also to provide practical insights and implementation guidelines tailored to resource-constrained edge devices.

AI and Data Science in Healthcare 5.0

1st Edition
December 1, 2025
Olfa Boubaker
English

AI and Data Science in Healthcare 5.0 delves into the innovative developments in Healthcare 5.0, focusing on smart medical robots, devices, and connected hospitals. It explores the role of robotics in modern healthcare, including advanced wearables enhanced by deep learning. The volume also addresses the integration of blockchain technology, IoT, and cloud computing in healthcare, emphasizing real-time applications in precision healthcare. The discussion extends to energy optimization in smart hospitals, federated learning for IoMT networks, and advanced patient monitoring systems.The volume concludes with an overview of the future opportunities and challenges in Healthcare 5.0.

Advances in Image Processing, Reliability, and Artificial Intelligence

1st Edition
November 16, 2025
Mario J. Divan + 4 more
English

Advances in Image Processing, Reliability, and Artificial Intelligence: Data Centred-Techniques and Applications in Edge Computing provides a clear outlook of the mechanisms, risks, challenges, and opportunities in system reliability for image processing and AI applications running on edge devices. It provides Best Known Configuration (BKC) and Methods (BKM) while discussing trends and future works based on current research. The content serves as a reference for practitioners and provides a state-of-the-art for researchers in the area. It provides foundations to analyse and replicate different applications through use cases. It tackles concerns for how reliability aspects (i.e., fault tolerance, availability, maturity, and recoverability) are addressed for applications running in an environment that is not fully controlled and exposed to environmental variations.

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

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health