This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring. Features: Provides a state-of-the-art computer vision application in the digital health care industry Reviews advances in computer vision and data science technologies for analyzing information on human function and disability Includes practical implementation of computer vision application using recent tools and software Explores computer vision-enabled medical/clinical data security in the cloud Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.

In the dynamic environment of healthcare, the fusion of Computational Intelligence and Healthcare Industry 4.0 has enabled remarkable advancements in disease detection and analysis. However, a critical challenge persists – the limitations of current computational intelligence approaches in dealing with small sample sizes. This setback hampers the performance of these innovative models, hindering their potential impact on medical applications. As we stand at the crossroads of technological innovation and healthcare evolution, the need for a solution becomes paramount. Advances in Computational Intelligence for the Healthcare Industry 4.0 is a comprehensive guide addressing the very heart of this challenge. Designed for academics, researchers, healthcare professionals, and stakeholders in Healthcare Industry 4.0, this book serves as a source of innovation. It not only illuminates the complexities of computational intelligence in healthcare but also provides a roadmap for overcoming the limitations posed by small sample sizes. From fundamental principles to innovative concepts, this book offers a holistic perspective, shaping the future of healthcare through the lens of computational intelligence and Healthcare Industry 4.0.

An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin—an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system’s behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI’s capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals.

This book presents different stages of Industrial Revolution in artificial intelligence and its impact on industry 4.0 and Healthcare. It contains chapters prepared for the industrial landscape which is being transformed to the fourth stage with the rise of autonomous robots, contemporary automation, cyber-physical systems, the Internet of things, and the Internet of services for examining the circumstances of health care system for the future. It highlights the emerging trends in integration of different intelligent manufacturing systems and advanced information technologies. Additionally, understanding of the real-world issues using artificial intelligence and the solutions discussed in this book help the enormous numbers of techniques which can be applied for effective diagnosis and predicting diseases from health care data.

Health 4.0 is a term that has derived from the Fourth Industrial Revolution (Industry 4.0), as it pertains to the healthcare industry. This book offers a novel, concise, but at the same time, broad picture of the challenges that the technological revolution has created for the healthcare system. It offers a comprehensive view of health sector actors’ interaction with the emerging new technology, which is disrupting the status quo in health service delivery. It explains how these technological developments impact both society and healthcare governance. Further, the book addresses issues related to key healthcare system stakeholders: the state, patients, medical professionals, and non-governmental organizations. It also examines areas of healthcare system adaptiveness and draws its conclusions by analysing recent health policy changes in different countries across the Americas, Europe, and Asia. The authors offer an innovative approach to the subject by identifying the critical determinants of successful implementation of the Fourth Industrial Revolution’s outcomes in practice, on both a macro- and microlevel. The macrolevel analysis is focused on essential factors of healthcare system adaptiveness for Health 4.0, while the microlevel relates to patients’ expectations with a particular emphasis on senior citizens. The book will appeal to academics, researchers, and students, across a wide range of disciplines, such as health economics, health sciences, public policy, public administration, political science, public governance, and sociology. It will also find an audience among healthcare professionals and health and social policymakers due to its recommendations for implementing Industry 4.0 into a healthcare system.

Health is regarded as one of the global challenges for mankind. Healthcare is a complex system that covers processes of diagnosis, treatment, and prevention of diseases. It constitutes a fundamental pillar of the modern society. Modern healthcare is technological healthcare. Technology is everywhere. This book focuses on twenty-one emerging technologies in the healthcare industry. An emerging technology is one that holds the promise of creating a new economic engine and is trans-industrial. Emerging technological trends are rapidly transforming businesses in general and healthcare in particular in ways that we find hard to imagine. Artificial intelligence (AI), machine learning, robots, blockchain, cloud computing, Internet of things (IoT), and augmented & virtual reality are some of the technologies at the heart of this revolution and are covered in this book. The convergence of these technologies is upon us and will have a huge impact on the patient experience

This book includes high-quality research on various aspects of intelligent interactive multimedia technologies in healthcare services. The topics covered in the book focus on state-of-the-art approaches, methodologies, and systems in the design, development, deployment, and innovative use of multimedia systems, tools, and technologies in healthcare. The volume provides insights into smart healthcare service demands. It presents all information about multimedia uses in e-healthcare applications. The book also includes case studies and self-assessment problems for readers and future researchers. This book proves to be a valuable resource to know how AI can be an alternative tool for automated and intelligent analytics for e-healthcare applications.

DIGITIZATION OF HEALTHCARE DATA USING BLOCKCHAIN The book gives a detailed description of the integration of blockchain technology for Electronic Health Records and provides the research challenges to consider in various disciplines such as supply chain, drug discovery, and data management. The aim of the book is to investigate the concepts of blockchain technology and its association with the recent development and advancements in the medical field. Moreover, it focuses on the integration of workflow strategies like NLP, and AI which could be adopted for boosting the clinical documentation and electronic healthcare records (EHR) usage by bringing down the physician EHR data entry. Also, the book covers the usage of smart contracts for securing patient records. Digitization of Healthcare Data Using Blockchain presents the practical implementations that deal with developing a web framework for building highly usable healthcare applications, a simple blockchain-powered EHR system. Audience Researchers in information technology, artificial intelligence, electronics engineering, medical informatics, as well as policymakers and healthcare providers and management systems.

The Internet of Things (IoT) and blockchain are two new technologies that combine elements in many ways. A system where the virtual and physical worlds interact is created by integrating pervasive computing, ubiquitous computing, communication technologies, sensing technologies, Internet Protocol, and embedded devices. A massive number of linked devices and vast amounts of data present new prospects for developing services that can directly benefit the economy, environment, society, and individual residents. Due to the size of IoT and insufficient data security, security breaches may have a huge impact and negative effects. IoT not only connects gadgets but also people and other entities, leaving every IoT component open to a wide variety of assaults. The implementation and application of IoT and blockchain technology in actual scientific, biomedical, and data applications are covered in this book. The book highlights important advancements in health science research and development by applying the distinctive capabilities inherent to distributed ledger systems. Each chapter describes the current uses of blockchain in real-world data collection, medicine development, device tracking, and more meaningful patient interaction. All of these are used to create opportunities for expanding health science research. This paradigm change is studied from the perspectives of pharmaceutical executives, biotechnology entrepreneurs, regulatory bodies, ethical review boards, and blockchain developers. Key Features: Provides a foundation for the implementation process of blockchain and IoT devices based on healthcare-related technology Image processing and IoT device researchers can correlate their work with other requirements of advanced technology in the healthcare domain Conveys the latest technology, including artificial intelligence and machine learning, in healthcare-related technology Useful for the researcher to explore new things like security, cryptography, and privacy in healthcare related technology Tailored for people who want to start in healthcare-related technology with blockchain and IoT This book is primarily for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, and biomedical engineering.

This book aims to demonstrate the benefits of implementing Industry 4.0 in healthcare services and to recommend a framework to support this implementation. Key topics in this book include: (1) Discovering emerging technologies and techniques to support Healthcare 4.0, this includes the Internet of Things (IOT) , Big data analytics, Blockchain, Artificial Intelligence (AI) , Optimisation and Predictive Analytics; (2) Illustrating some examples of such advanced implementation in Healthcare 4.0; (3) Recommending a development process to develop health technology start-ups and entrepreneurial activities; and (4) Discuss the transformation methodology used to redesign healthcare processes in order to overcome the challenges of implementing a Healthcare 4.0 project.