Agbotiname Lucky Imoize – författare

Federated Learning for Digital Healthcare Systems critically examines the key factors that contribute to the problem of applying machine learning in healthcare systems and investigates how federated learning can be employed to address the problem. The book discusses, examines, and compares the applications of federated learning solutions in emerging digital healthcare systems, providing a critical look in terms of the required resources, computational complexity, and system performance.In the first section, chapters examine how to address critical security and privacy concerns and how to revamp existing machine learning models. In subsequent chapters, the book's authors review recent advances to tackle emerging efficient and lightweight algorithms and protocols to reduce computational overheads and communication costs in wireless healthcare systems. Consideration is also given to government and economic regulations as well as legal considerations when federated learning is applied to digital healthcare systems.

Provides insights into real-world scenarios of the design, development, deployment, application, management, and benefits of federated learning in emerging digital healthcare systemsHighlights the need to design efficient federated learning-based algorithms to tackle the proliferating security and patient privacy issues in digital healthcare systemsReviews the latest research, along with practical solutions and applications developed by global experts from academia and industry

Cybersecurity Defensive Walls in Edge Computing dives into the creation of robust cybersecurity defenses for increasingly vulnerable edge devices. This book examines the unique security challenges of edge environments, including limited resources and potentially untrusted networks, providing fundamental concepts for real-time vulnerability detection and mitigation through novel system architectures, experimental frameworks, and AI/ML techniques. Researchers and industry professionals working in cybersecurity, edge computing, cloud computing, defensive technologies, and threat intelligence will find this to be a valuable resource that illuminates critical aspects of edge-based security to advance theoretical analysis, system design, and practical implementation of defensive walls. With a focus on fast-growing edge application scenarios, this book offers valuable insights into strengthening real-time security for the proliferation of interconnected edge devices.Provides researchers with insights into real-world scenarios of the design, development, deployment, application, management, and benefits of cybersecurity defensive walls in edge computingDiscusses critical cybersecurity defensive walls and their applications to resolve security and privacy issues which affect all parties in edge computing and provide practical learning-based solutions to solve these problemsPresents well-structured chapters from industry experts and global researchers who consider unique security challenges, including limited resources, diverse device types, and potentially untrusted network environments

The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems.Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions.This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others.

The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems.Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions.This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others.

The text provides a comprehensive study of the application of advanced artificial intelligence (AI) in next-generation wireless communications with a focus on theory, standardization, and core development. It further highlights AI-enabled intelligent architecture for sixth-generation (6G) networks to realize smart resource management, automatic network adjustment, and intelligent service layers. The book covers artificially assisted non-orthogonal multiple access schemes for 6G communication.This book:Discusses the use of AI in various aspects of wireless communications, including channel modeling, signal detection, channel coding design, and resource managementExplores technical challenges in the ubiquitous fifth-generation (5G) wireless networks and the prospects of introducing artificial intelligence-based techniques in the envisioned 6G wireless networksPresents potential issues in AI-enabled approaches in wireless communicationsCovers AI-enabled energy efficiency optimization and cross-layer optimization in the next-generation wireless networksExplains artificially empowered security and privacy schemes in next-generation wireless networks and next-generation mobile managementIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

The book covers the exploitation of computational models for effectively developing and managing large-scale wireless communication systems. The goal is to create and establish computational models for seamless human interaction and efficient decision-making in beyond 5G wireless systems.Computational Modeling and Simulation of Advanced Wireless Communication Systems looks to create and establish computational models for seamless human interaction and efficient decision-making in the beyond 5G wireless systems. This book presents the design and development of several computational modeling techniques and their applications in wireless communication systems. It examines shortcomings and limitations of the existing computational models and offers solutions to revamp the traditional architecture toward addressing the vast network issues in wireless systems. The book addresses the need to design efficient computational and simulation models to address several issues in wireless communication systems, such as interference, pathloss, delay, traffic outage, and so forth. It discusses how theoretical, mathematical, and experimental results are integrated for optimal system performance to enhance the quality of service for mobile subscribers.Further, the book is intended for industry and academic researchers, scientists, and engineers in the fields of wireless communications and ICTs. It is structured to present a practical guide to wireless communication engineers, IT practitioners, researchers, students, and other professionals.

This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field.Key Features:• Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics.• Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment.• Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment.• Provides a systematic overview of the state-of-the-art research efforts.• Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment.This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.

This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field.Key Features:• Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics.• Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment.• Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment.• Provides a systematic overview of the state-of-the-art research efforts.• Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment.This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.

The text provides a comprehensive study of the application of advanced artificial intelligence (AI) in next-generation wireless communications with a focus on theory, standardization, and core development. It further highlights AI-enabled intelligent architecture for sixth-generation (6G) networks to realize smart resource management, automatic network adjustment, and intelligent service layers. The book covers artificially assisted non-orthogonal multiple access schemes for 6G communication.This book:Discusses the use of AI in various aspects of wireless communications, including channel modeling, signal detection, channel coding design, and resource managementExplores technical challenges in the ubiquitous fifth-generation (5G) wireless networks and the prospects of introducing artificial intelligence-based techniques in the envisioned 6G wireless networksPresents potential issues in AI-enabled approaches in wireless communicationsCovers AI-enabled energy efficiency optimization and cross-layer optimization in the next-generation wireless networksExplains artificially empowered security and privacy schemes in next-generation wireless networks and next-generation mobile managementIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

This book offers a comprehensive exploration of cutting-edge research and developments in the field of cybersecurity. It presents a curated collection of chapters that reflect the latest in empirical data approximation, malware recognition, information security technologies, and beyond.Advancements in Cybersecurity: Next-Generation Systems and Applications offers readers a broad perspective on the multifaceted challenges and solutions in contemporary cybersecurity through topics ranging from the application of blockchain technology in securing information systems, to the development of new cost functions for the iterative generation of cryptographic components. The book not only addresses technical aspects but also provides insights into the theoretical frameworks and practical applications that underpin the development of robust cybersecurity systems. It explores the optimization of algorithms for generating nonlinear substitutions, the application of machine learning models for security evaluation, and the implementation of deep learning techniques for detecting sophisticated cyber-attacks. Through its in-depth analysis and forward-looking perspectives, this book contributes significantly to advancing cybersecurity research and practice, paving the way for a safer digital future.This book is designed to serve as an essential resource for researchers, practitioners, policymakers, and engineers in the fields of ICT, next-generation computing and IT security, including cryptography, AI/ML/DL, cyber resilience, network security, threat modeling and risk assessment, digital forensics, secure software development, hardware security, and human-centric security.

This handbook offers a thorough examination of the ever-changing landscape of cybersecurity, exploring the critical challenges and innovative solutions that shape the field during the era of digital transformation. It features a compilation of in-depth chapters written by top experts in cybersecurity, providing a detailed evaluation of both the theoretical and practical aspects of securing advanced systems and applications.Handbook of Cybersecurity: Challenges and Solutions for Emerging Technologies provides researchers and academics with fresh insight into the practical applications, management, and benefits of advanced cybersecurity systems. The handbook explores the necessity of developing efficient computational and simulation models to tackle various cybersecurity challenges. It also critically examines the shortcomings of current cybersecurity systems and proposes innovative solutions to modernize traditional architectures to effectively address existing cybersecurity issues in real-world scenarios.Written in clear and accessible language, this handbook features numerous illustrations and tables to enhance readability and comprehension for researchers, industry professionals, graduates, postgraduate students, and academicians.

This book begins by exploring the foundations of wireless communication systems, providing a detailed overview of the principles, protocols, and technologies that underpin modern wireless networks. It then progresses to discuss emerging trends and technologies, such as fifth generation (5G) and sixth generation (6G) networks, the Internet of Things (IoT), and artificialiIntelligence (AI), and their potential contributions to green environments. Features:Emphasizes green communications for energy-efficient wireless systems and networks, providing in-depth insights into sustainable practices in wireless technology.Investigates strategies for efficient utilization of hardware resources such as spectrum allocation, power management, and antenna design.Explores how advanced wireless systems can be harnessed to create eco-friendly solutions for a greener world.Explains advanced encryption techniques, authentication protocols, and intrusion detection systems specifically tailored for safeguarding wireless communication networks operating in open channels.Discusses the application of wireless technologies in the realm of environmental conservation and biodiversity preservation.It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, telecommunication, wireless communication, and environmental engineering.

This handbook bridges the gap between theory and practical applications, providing foundational knowledge and actionable insights into the use of AI in future wireless networks. The book is a comprehensive guide to developing, deploying, and managing intelligent wireless systems, contributing to the global push toward a hyper-connected world.Handbook of AI in Wireless Networks: Foundations, Techniques, and Emerging Applications explores the intersection of artificial intelligence (AI) and wireless communication systems, providing a comprehensive guide to how AI transforms the design, management, and optimisation of wireless networks. Additionally, the book discusses emerging trends in AI-aided wireless communication systems, including integrated sensing and communications, intelligent spectrum management for dynamic allocation, traffic scheduling for optimal resource allocation, energy efficiency, security and privacy, and ethical considerations. The book offers innovative approaches to solving real-world wireless network challenges related to spectrum management, network optimisation, traffic management, security, and privacy, leveraging cutting-edge AI algorithms.The book is written for a diverse audience, including researchers, academics, industry professionals, and policymakers in wireless communications, artificial intelligence, and network systems. It is particularly relevant to engineers and practitioners involved in designing, developing, and deploying next-generation wireless networks, as well as to graduate and postgraduate students specializing in AI, telecommunications, and computer networks.

The book begins by exploring the fundamentals of green wireless communication systems, providing a detailed overview of the core principles and candidate enabling technologies for 6G. It then discusses innovative technologies and the integration of artificial intelligence (AI)- empowered algorithms into wireless networks to promote green, sustainable environments. Additionally, the handbook presents interdisciplinary approaches and emphasizes the need for hybrid solutions to develop green and secure 6G network infrastructure.This Book:Examines the role of AI in shaping the architecture and protocols of emerging wireless systems, as well as key application areas such as traffic prediction, dynamic spectrum access, and energy efficiency.Discusses the incorporation of AI-based algorithms into wireless networks, enabling optimal channel estimation, traffic prediction, interference management, and resource allocation in green wireless communication systems.Explains advanced cryptographic techniques and physical layer security architecture specifically tailored for safeguarding wireless communication networks operating in open channels.Explores the latest trends in the application of AI in wireless networks and highlights the path toward AI-enabled wireless communication systems.Identifies future challenges and provides a roadmap for the future adoption of AI in advanced wireless communication systems. The book is primarily written for senior undergraduates, graduate students, academic researchers, and professionals in electrical engineering, electronics and communications engineering, telecommunication, wireless communication, and environmental engineering.

Authoritative resource discussing the development of advanced massive multiple input multiple output (MIMO) techniques and algorithms for application in 6G Massive MIMO for Future Wireless Communication Systems analyzes applications and technology trends for massive multiple input multiple output (MIMO) in 6G and beyond, presenting a unified theoretical framework for analyzing the fundamental limits of massive MIMO that considers several practical constraints. In addition, this book develops advanced signal-processing algorithms to enable massive MIMO applications in realistic environments. The book looks closer at applying techniques to massive MIMO in order to meet practical network constraints in 6G networks, such as interference, pathloss, delay, and traffic outage, and provides new insights into real-world deployment scenarios, applications, management, and associated benefits of robust, provably secure, and efficient security and privacy schemes for massive MIMO wireless communication networks. To aid in reader comprehension, this book includes a glossary of terms, resources for further reading via a detailed bibliography, and useful figures and summary tables throughout. With contributions from industry experts and researchers across the world and edited by two leaders in the field, Massive MIMO for Future Wireless Communication Systems includes information on: Signal processing algorithms for cell-free massive MIMO systems and advanced mathematical tools to analyze multiuser dynamics in wireless channelsBit error rate (BER) performance comparisons of different detectors in conventional cell-free massive MIMO systemsEnhancement of massive MIMO using deep learning-based channel estimation and cell-free massive MIMO for wireless federated learningLow-complexity, self-organizing, and energy-efficient massive MIMO architectures, including the prospects and challenges of Terahertz MIMO systemsMassive MIMO for Future Wireless Communication Systems is an essential resource on the subject for industry and academic researchers, advanced students, scientists, and engineers in the fields of MIMO, antennas, sensing and channel measurements, and modeling technologies.

New insights into trends, deployments, applications, and associated benefits of reconfigurable intelligent surfaces (RIS) in emerging wireless communication systems Reconfigurable Intelligent Surfaces for 6G and Beyond Wireless Networks analyzes the design and applications of RIS in 6G and beyond, such as aiding efficient wireless signal transmission from the transmitter to the receiver while considering several practical constraints. In addition, the book offers advanced signal-processing algorithms to enable RIS applications in realistic environments and leverages advanced mathematical tools and machine learning algorithms to analyze RIS dynamics in evolving wireless networks. Written in an easy-to-understand format, this book addresses the need to design energy- and spectral-efficient RIS models to address several network issues, including interference, pathloss, delay, traffic outage, etc. It also discusses critical security and privacy issues affecting all stakeholders in the wireless ecosystem, providing practical deep learning-based solutions to address these problems appropriately. This book also addresses critical concepts, design principles, applications, and issues with RIS, shedding light on the recent progress and advancement in RIS-assisted wireless networks for 6G and beyond. With contributions from experts and researchers from across the globe, this invaluable resource includes information on: Emerging applications and potential use cases of reconfigurable intelligent surfaces in advanced wireless communication systemsChannel modeling and propagation measurements in RIS-based wireless communication systemsEnergy and spectral efficiency and rate fairness for RIS-aided multiuser massive MIMO systemsPerformance optimization of multiple RIS-assisted multiuser MIMO communication systemsAnalytical phase-shift and amplitude element optimization for energy-efficient active RIS-aided massive MIMO systemsPhysical layer security architecture and frameworks for RIS-aided wireless communication systemsRIS deployment in terrestrial and non-terrestrial wireless communication systemsApplication of AI and ML techniques for intelligent power control in RIS-empowered wireless communication systemsReconfigurable Intelligent Surfaces for 6G and Beyond Wireless Networks is an essential up-to-date reference on the subject for industry and academic researchers, scientists, and engineers in the fields of wireless communications, ICTs, MIMO, antennas, sensing, channel measurements, and modeling technologies, as well as engineers and professionals involved in RIS-assisted wireless networks.

An expert compilation of on-device training techniques, regulatory frameworks, and ethical considerations of TinyML design and development In Tiny Machine Learning: Design Principles and Applications, a team of distinguished researchers delivers a comprehensive discussion of the critical concepts, design principles, applications, and relevant issues in Tiny Machine Learning (TinyML). Expert contributors introduce a new low power resource, offering vast applications in IoT devices with system-algorithm co-design. Tiny Machine Learning explores TinyML paradigms and enablers, TinyML for anomaly detection, and the learning panorama under TinyML. Readers will find explanations of TinyML devices and tools, power consumption and memory in IoT microcontrollers, and lightweight frameworks for TinyML. The book also describes TinyML techniques for real-time and environmental applications. Additional topics covered in the book include: A thorough introduction to security and privacy techniques for TinyML devices, including the implementation of novel security schemesIncisive explorations of power consumption and memory in IoT MCUs, including ultralow-power smart IoT devices with embedded TinyMLPractical discussions of TinyML research targeting microcontrollers for data extraction and synthesisPerfect for industry and academic researchers, scientists, and engineers, Tiny Machine Learning will also benefit lecturers and graduate students interested in machine learning.

Medical decision support systems (MDSS) are computer-based programs that analyse data within a patient's healthcare records to provide questions, prompts, or reminders to assist clinicians at the point of care. Inputting a patient's data, symptoms, or current treatment regimens into an MDSS, clinicians are assisted with the identification or elimination of the most likely potential medical causes, which can enable faster discovery of a set of appropriate diagnoses or treatment plans. Explainable AI (XAI) is a "white box" model of artificial intelligence in which the results of the solution can be understood by the users, who can see an estimate of the weighted importance of each feature on the model's predictions, and understand how the different features interact to arrive at a specific decision.This book discusses XAI-based analytics for patient-specific MDSS as well as related security and privacy issues associated with processing patient data. It provides insights into real-world scenarios of the deployment, application, management, and associated benefits of XAI in MDSS. The book outlines the frameworks for MDSS and explores the applicability, prospects, and legal implications of XAI for MDSS. Applications of XAI in MDSS such as XAI for robot-assisted surgeries, medical image segmentation, cancer diagnostics, and diabetes mellitus and heart disease prediction are explored.

Fifth generation (5G) wireless networks are now commercialized, and the research focus has shifted towards sixth generation (6G) wireless systems. The integration of sensor nodes and massive machine type communication (MTC) devices (MDs) in ubiquitous 5G networks has facilitated the design of critical enabling technologies to support billions of data-hungry applications. By leveraging sensor nodes in wireless sensor networks (WSNs), sensitive user information can be harvested and transmitted to receivers via WSN-assisted channels, which are often not well secured. Consequently, sensitive user information can be intercepted and used unlawfully. The security and confidentiality measures used for data transmission over existing 5G WSN-assisted channels are limited. 6G systems are envisaged to face fiercer security challenges. In 6G wireless networks, a new set of sensing and precise localization techniques are predicted. Thus, the need to secure user information against adversarial attacks needs to be implemented at the design stage.The book proposes viable solutions to revamp traditional security architecture by addressing critical security challenges in commercialized 5G and envisioned 6G wireless communication systems. Expert contributors bring new insights into real-world scenarios for the deployment, applications and management of robust, secure, and efficient security schemes for massive devices in 6G wireless networks. Finally, the book discusses critical security and privacy issues affecting the wireless ecosystem and provides practical AI-based solutions.Security and Privacy Schemes for Dense 6G Wireless Communication Networks is an essential reference for industry and academic researchers; scientists, engineers, lecturers and advanced students in the fields of cybersecurity wireless communication and networking, network security, computing, data science, AI/ML/DL, and sensing, as well as cybersecurity professionals and 6G standardization experts.

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.

Billions of wireless applications are proliferating in the global space. The novel wireless systems to support these applications need to satisfy several user-defined metrics to ensure quality of physical experience, quality of service, low latency and ultra-high reliability. Enabling technologies are being developed in order to meet these rate-hungry requirements.Managing these complex wireless and computing resources requires a proactive analysis of the core wireless systems, especially in the metaverse, which is a virtual model of the physical world systems. The metaverse concept is intended to be self-sustainable and facilitates the seamless operation of wireless systems at minimal operational costs for the efficient management of wireless system resources. It is gaining widespread popularity using technologies such as advanced optimization theory, digital twins, virtual reality, machine learning, and blockchain.This book presents a comprehensive overview of advanced metaverse wireless communication systems. The authors highlight the technology enablers and critical design aspects, emphasize how the metaverse can support wireless systems but also show how wireless systems can empower the metaverse. They address critical concerns covering theoretical analysis, novel system architecture design and new implementation methodologies, emerging application scenarios, experimental frameworks, and reliability, security, privacy, technical, and ethical considerations, viable solutions, as well as open challenges, the social impacts of the metaverse concept and future perspectives.Offering a range of international perspectives from researchers in the field, this book is intended for researchers from academia and industry, and scientists, engineers, lecturers and advanced students in the fields of wireless and mobile communications, networking, computing, data science, AI/ML/DL, multimedia, haptics, sensing, CPS and immersive technologies.

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.

The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems.

The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems.

The book discusses how Unmanned Aerial Vehicles (UAVs) can leverage the sub-6 GHz massive MIMO to address cell selection and interference issues in future wireless networks.

The book discusses how Unmanned Aerial Vehicles (UAVs) can leverage the sub-6 GHz massive MIMO to address cell selection and interference issues in future wireless networks.

This book explores the integration of AI, data science, and emerging technologies to create innovative, practical solutions for smart environments.

The Intersection of Artificial Intelligence, Data Science, and Cutting-Edge Technologies: From Concepts to Applications in Smart Environments delves into the convergence of AI, data science, and innovative technologies within the realm of smart environments.

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.