Joseph Bamidele Awotunde – författare

Artificial Intelligence-Driven Metaverse Integration in Smart Healthcare: Advancing Personalized and Predictive Medical Capabilities offers a comprehensive exploration of cutting-edge technologies and their transformative potential in healthcare. The book delves into the application of artificial intelligence (AI) in the healthcare sector, examining machine learning algorithms, natural language processing, and computer vision to enhance healthcare delivery. It also introduces the metaverse, an immersive virtual environment, and explores its integration into medical practices, patient engagement, and health-related experiences. This is an invaluable resource for researchers and practitioners in biomedical fields, health informatics, and personalized and predictive medical systems.In 26 chapters, the book discusses how the convergence of AI and the metaverse contributes to the development of smart healthcare systems that are more efficient, accessible, and personalized. It highlights AI's role in customizing medical treatments, diagnostics, and patient care, leading to more effective healthcare experiences. Additionally, it explores predictive analytics and modeling using AI to prevent diseases, optimize treatments, and improve healthcare outcomes. Providing insights into the current state of AI in healthcare and the potential of metaverse integration, the book includes case studies, practical applications, and future perspectives.Explores the advancement of Artificial Intelligence in healthcare, its prospective for metaverse integration, and its potential to enhance personalized and predictive medical capabilitiesGives insights on how artificial intelligence and the metaverse can be leveraged to provide more personalized healthcare solutionsAddresses the technological hurdles, ethical considerations, and privacy concerns associated with integrating AI and the metaverse into healthcare

Company Digital Twins, a new volume in the Advances in Digital Twin Computing and Sensor Networks series, explores virtual companies based on digital twin technologies. The book covers foundational concepts, emerging trends, underlying technologies, practical applications, future directions, data security, privacy concerns, integration issues, and the scalability of digital twins across large companies. It is essential reading for anyone who needs to benefit from the capabilities of digital twins within the organization. The timeliness of this book lies in the rapid, current digital transformation and the increasing complexity of systems requiring real-time, intelligent management to achieve competitive advantages and sustainability goals.The concept of the digital twin, a virtual representation of a physical system, has gained significant attention due to advancements in Artificial Intelligence, Internet of Things, and data analytics. It plays a crucial role in enhancing efficiency, sustainability, and decision-making across industries, such as manufacturing, healthcare, and urban planning.Discusses how companies use digital twins for real-time decision-making and strategic foresightCovers sectors that are embracing this technology, including manufacturing, healthcare, smart cities, agriculture, transportation, retail, etc.Highlights trends in digital twin applications for improving efficiency, sustainability, and innovation in companiesExplores technological components such as Internet of Things, Artificial Intelligence, big data analytics, blockchain, and cloud computingExamines challenges such as data security, integration complexity, and scalability, and offers insights into future developments

Fundamentals of Fog Computing and the Internet of Things for Smart Healthcare explores the intersection of two transformative technologies, fog computing and the IoT, shedding light on how they are revolutionizing healthcare. The book serves as an essential guide for researchers and graduate students, explaining the underlying concepts, operational benefits, and potential challenges of these technologies. By delving into how fog computing enhances real-time data processing, the book's authors provide invaluable insights into the practical applications of these advancements in the healthcare industry.Additionally, together with its companion book, Advances in Fog computing and the Internet of Things for Smart Healthcare, the series provides a comprehensive understanding of how these technologies are enabling more efficient, personalized, and accessible healthcare services. By facilitating smart applications and services across various industries, fog computing optimizes performance, latency, privacy, and overall system efficiency, ultimately contributing to the development of more effective and responsive IoT ecosystems.Discusses the fundamentals of fog computing, IoT technology, and their applications in healthcare, offering both technical and non-technical readers a clear understanding of the conceptsOffers in-depth insights into the technical architecture, networking protocols, security considerations, and data management strategies, thus catering to IT professionals and researchersExplores how fog computing and IoT can be integrated to optimize resource allocation, patient care, and operational efficiency

Advances in Fog Computing and the Internet of Things for Smart Healthcare delves into the transformative impact of fog computing and IoT on modern healthcare systems. This comprehensive guide educates researchers and graduate students on the fundamental concepts of these technologies, illustrating their practical applications in healthcare. Real-world use cases showcase the technologies' ability to enhance patient monitoring and personalized medicine. The book also addresses significant challenges such as privacy, security, data management, and regulatory compliance, providing strategies for overcoming them.Alongside its companion book, Fundamentals of Fog Computing and the Internet of Things for Smart Healthcare, this volume empowers various industries to leverage IoT technologies while optimizing performance and system efficiency. It highlights the crucial role of fog computing in processing data closer to the source, ensuring faster and more efficient data processing and contributing to the creation of effective IoT ecosystems. This synergy between fog computing and IoT facilitates smarter applications and services, advancing the landscape of healthcare with more efficient, personalized, and accessible services.Provides a comprehensive introduction to fog computing, IoT technology, and their applications in healthcare, offering both technical and non-technical readers a clear understanding of the conceptsShowcases real-world case studies and examples of fog computing and IoT implementations in healthcare settings, illustrating practical benefits and challengesProvides strategic insights into how fog computing and IoT can be integrated to optimize resource allocation, patient care, and operational efficiencyExplores the ethical, privacy, and regulatory challenges associated with implementing these technologies in healthcare, guiding readers through the potential pitfallsDiscusses emerging trends and potential future developments at the intersection of fog computing, IoT, and healthcare, equipping readers with forward-looking perspectives

Industry 4.0 and 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.Computational Intelligence in Industry 4.0 and 5.0 Applications examines applications that merge three key disciplines: computational intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using Industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective.Industry 4.0 integrates data and intelligent automation into manufacturing, using technologies like CI, the IoT, the IIoT, and cloud computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industries 4.0 and 5.0 are undergoing significant transformations due to advances in applying artificial intelligence (AI), big data analytics, telecommunication technologies, and control theory. These applications are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face such technical challenges as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these, this book examines such CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and big data analytics that further enhance CI-based solutions in Industry 4.0 and 5.0 systems.

Industry 4.0 and Industry 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.Computational Intelligence for Analysis of Trends in Industry 4.0 and 5.0 examines the trends in applications that merge three key disciplines: Computational Intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective.Industry 4.0 integrates data and intelligent automation into manufacturing, using technologies like CI, Internet of Things (IoT), IIoT, and cloud computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industry 4.0 and Industry 5.0 are undergoing significant transformations due to advances in applying artificial intelligence (AI), big data analytics, telecommunication technologies, and control theory. These trends are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face technical challenges such as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these issues, this book examines trends such as CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and big data analytics that further enhance CI-based solutions in Industry 4.0 and Industry 5.0 systems.

Industry 4.0 and 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.Computational Intelligence in Industry 4.0 and 5.0 Applications examines applications that merge three key disciplines: computational intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using Industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective.Industry 4.0 integrates data and intelligent automation into manufacturing, using technologies like CI, the IoT, the IIoT, and cloud computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industries 4.0 and 5.0 are undergoing significant transformations due to advances in applying artificial intelligence (AI), big data analytics, telecommunication technologies, and control theory. These applications are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face such technical challenges as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these, this book examines such CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and big data analytics that further enhance CI-based solutions in Industry 4.0 and 5.0 systems.

The expansion of telehealth services is enabling healthcare professionals to consult, diagnose, advise or perform tasks remotely, enabling them to treat more patients in their own homes or consult on cases on the other side of the world. The security of sensitive user information is critical to effective and efficient delivery of healthcare services. Artificial intelligence (AI) and blockchain technology are identified as key drivers of emerging telehealth systems, enabling efficient delivery of telehealth services to billions of patients globally. Specifically, AI facilitates the processing and analysis of complex telehealth data, and blockchain technology offers decentralised, transparent, traceable, reliable, trustful, and provable security to telehealth systems.This edited book reviews security and privacy issues in traditional telehealth systems and focuses on the technical considerations, potential opportunities and critical challenges currently inhibiting the adoption of AI and blockchain in telehealth systems. The book presents case studies which highlight critical lessons and considers the prospects and societal benefits of AI and blockchain, while providing suitable recommendations for designing future AI and blockchain-based telehealth systems.Artificial Intelligence and Blockchain Technology in Modern Telehealth Systems is suited to researchers and computer engineers working in healthcare delivery, telemedicine, cybersecurity, data science, AI/ML and those in related fields.

Emerging healthcare networks are interconnected physical systems that use cyber technologies for interaction and functionality. The proliferation of massive internet-of-things (IoT) devices enables remote and distributed access to cutting-edge diagnostics and treatment options in modern healthcare systems. New security vulnerabilities are emerging due to the increasing complexity of the healthcare architecture, in particular, threats to medical devices and critical infrastructure pose significant concerns owing to their potential risks to patient health and safety. In recent times, patients have been exposed to high risks from attacks capable of disrupting critical medical infrastructure, communications facilities, and services, interfering with medical devices, or compromising sensitive user data.This book seeks to present cyber risk and vulnerability models, considering a number of threats and examining how effective regulations could help guarantee medical device fidelity and trust. The book discusses the application of artificial intelligence and machine learning to provide practical learning-based solutions to address cyberattacks in emerging healthcare systems. The book focuses on the technical considerations, potential opportunities, critical cybersecurity challenges, the prospects and potential benefits of cybersecurity in emerging healthcare systems. Finally, the book presents case studies, highlighting critical lessons, and providing recommendations for designing AI-based cybersecurity architectures for emerging healthcare systems.Written by an international team of authors, this book is suitable for an audience of industry-based and academic researchers, scientists, and computer engineers working in data science, cybersecurity and wireless communications particularly those specialising in healthcare data science and those in related fields.

This book constitutes the refereed conference proceedings of the 7th International Conference on Emerging Technologies for Developing Countries, AFRICATEK 2024, held in Ilorin, Nigeria, during August 6–8, 2024.The 15 full papers included in this book were carefully reviewed and selected from 42 submissions. They were organized in the below following topics such as : Smart, Sustainable Cities and Climate Change Management; Innovation in Healthcare Systems; Environmental Monitoring, Smart Agriculture and Smart Education.

This book bridges cutting-edge technology with practical healthcare applications, offering readers a front-row seat to the transformation of patient care, diagnostics, training, and system management. These technologies enhance diagnostics, patient engagement, and care delivery by creating smarter, more connected, and patient-centric systems. This book is organized into four key sections. The first part focuses on AI’s role in diagnostics, predictive analytics, and early disease detection, showcasing how machine learning and data analysis improve accuracy and timeliness. The second part investigates metaverse applications, including virtual consultations, immersive therapies, and the design of mobile health (mHealth) solutions tailored for older adults, emphasizing accessibility and inclusivity. The third section presents integrated AI and metaverse solutions, such as digital twins, XR, edge computing, and real-time healthcare deployments, illustrating the potential for dynamic and intelligent care environments. The final part discusses critical issues surrounding data privacy, ethical governance, and security within virtual healthcare settings, highlighting blockchain-enabled approaches to safeguard sensitive information. Aimed at a broad audience of researchers, developers, healthcare providers, and policymakers, this book combines practical examples, theoretical approaches, and case studies to offer a comprehensive roadmap. The synthesis of these emerging technologies envisions a future healthcare paradigm that balances technological innovation with ethical considerations and patient-centered care principles. Whether you are a healthcare professional, technologist, policymaker, or innovator, this book provides invaluable insights into:AI in Smart Healthcare SystemsMetaverse in MedicineAI-Infused Metaverse SolutionsSecurity, Privacy, and EthicsPatient-Centric Healthcare EcosystemsImmersive Healthcare ExperiencesInclusive mHealth DesignEdge, Fog, and Cloud IntegrationNeuroimaging and Predictive Analytics