Dinh-Thuan Do – författare

Internet of Healthcare Things (IoHT) is an Internet of Things (IoT)-based solution that includes a network architecture which allows the connection between a patient and healthcare facilities. This book covers various research issues of smart and secure IoHT, aimed at providing solutions for remote healthcare monitoring using pertinent techniques. Applications of machine learning techniques and data analytics in IoHT, along with the latest communication and networking technologies and cloud computing, are also discussed. Features: Provides a detailed introduction to IoHT and its applications Reviews underlying sensor and hardware technologies Includes recent advances in the IoHT, such as remote healthcare monitoring and wearable devices Explores applications of data analytics/data mining in IoHT, including data management and data governance Focuses on regulatory and compliance issues in IoHTThis book is intended for graduate students and researchers in Bioinformatics, Biomedical Engineering, Big Data and Analytics, Data Mining, and Information Management, IoT and Computer and Electrical Engineering.

Internet of Healthcare Things (IoHT) is an Internet of Things (IoT)-based solution that includes a network architecture which allows the connection between a patient and healthcare facilities. This book covers various research issues of smart and secure IoHT, aimed at providing solutions for remote healthcare monitoring using pertinent techniques. Applications of machine learning techniques and data analytics in IoHT, along with the latest communication and networking technologies and cloud computing, are also discussed. Features: Provides a detailed introduction to IoHT and its applications Reviews underlying sensor and hardware technologies Includes recent advances in the IoHT, such as remote healthcare monitoring and wearable devices Explores applications of data analytics/data mining in IoHT, including data management and data governance Focuses on regulatory and compliance issues in IoHTThis book is intended for graduate students and researchers in Bioinformatics, Biomedical Engineering, Big Data and Analytics, Data Mining, and Information Management, IoT and Computer and Electrical Engineering.

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.

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 focuses on the integration of intelligent communication systems, control systems and devices related to all aspects of engineering and sciences.

It gathers selected papers presented at the 5th International Conference on Communication, Devices and Networking (ICCDN 2021), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on 15–16 December 2021.

It gathers selected papers presented at the 5th International Conference on Communication, Devices and Networking (ICCDN 2021), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on 15–16 December 2021.

It gathers selected papers presented at the 7th International Conference on Communication, Devices and Networking (ICCDN 2024), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on 19–20 January 2024.

This book covers recent trends in the field of devices, wireless communication and networking. It gathers selected papers presented at the 7th International Conference on Communication, Devices and Networking (ICCDN 2024), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on 19–20 January 2024. Gathering cutting-edge research papers prepared by researchers, engineers and industry professionals helps young and experienced scientists and developers alike to explore new perspectives and offers them inspirations on how to address real-world problems in the areas of electronics, communication, devices and networking.

It gathers selected papers presented at the 7th International Conference on Communication, Devices and Networking (ICCDN 2024), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on January 19–20, 2024.

This book covers recent trends in the field of devices, wireless communication and networking. It gathers selected papers presented at the 7th International Conference on Communication, Devices and Networking (ICCDN 2024), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on January 19–20, 2024. Gathering cutting-edge research papers prepared by researchers, engineers and industry professionals, it helps young and experienced scientists and developers alike to explore new perspectives and offers them inspirations on how to address real-world problems in the areas of electronics, communication, devices and networking.

It gathers selected papers presented at the 6th International Conference on Communication, Devices and Networking (ICCDN 2022), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on December 16–17, 2022.