Akash Kumar Bhoi – författare

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field.

The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision making.

This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning.

Focuses on data-centric operations in the Healthcare industry Provides the latest trends in healthcare data analytics and practical implementation outcomes of the proposed models Addresses real-time challenges and case studies in the Healthcare industry

5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realization of a smart-healthcare system. The book provides insights on 5G technologies, along with intelligent processing algorithms/processors that have been adopted for processing the medical data that would assist in addressing the challenges in computer-aided diagnosis and clinical risk analysis on a real-time basis. Each chapter is self-sufficient, solving real-time problems through novel approaches that help the audience acquire the right knowledge.

With the progressive development of medical and communication - computer technologies, the healthcare system has seen a tremendous opportunity to support the demand of today's new requirements.

Focuses on the advancement of 5G in terms of its security and privacy aspects, which is very important in health care systems Address advancements in signal processing and, more specifically, the cognitive computing algorithm to make the system more real-time Gives insights into various information-processing models and the architecture of layers to realize a 5G based smart health care system

Green Energy Systems: Design, Modelling, Synthesis and Applications provides a comprehensive introduction to the design, modeling, optimization and application of predictable and alternative energy systems. With a strong focus on the fundamentals, the book provides an overview of the energy potential and conversion topology of green energy sources, the design and analysis of off grid solar and wind energy sources, and their application in effective energy management in rural communities. Sections address energy systems from solar, wind, biomass, and hybrid energy sources, and include discussions of power electronic circuit topologies for energy conversion in both off and on grid systems.

The second part of the book addresses energy harvesting at different scales, with a particular emphasis on micro energy harvesting for low power electronics like wearable devices. A wide range of applications are also discussed, alongside their challenges and solutions. Finally, case studies are presented on select topics to give readers deeper insights into the real-world applications discussed.

Introduces the fundamental principles underlying green energy systems, their characterization, analysis, modelling, and evaluation Includes a wide range of applications of new functional materials for next-generation devices Provides supporting data and calculations alongside real-world case studies

Artificial Intelligence Applications for Brain-Computer Interfaces focuses on the advancements, challenges, and prospects of future technologies involving noninvasive brain-computer interfaces (BCIs). It includes the processing and analysis of multimodal signals, integrated computation-acquisition devices, and implantable neuro techniques. This book not only provides cross-disciplinary research in BCI but also presents divergent applications on telerehabilitation, emotion recognition, neuro-rehabilitation, cognitive workload assessments, and ambient assisted living solutions. In 15 chapters, this book describes how BCIs connect the brain with external devices like computers and electronic gadgets. It analyzes the neural signals from the brain to obtain insights from the brain patterns using multiple noninvasive wearable sensors. It gives insight into how sensor outcomes are processed through machine-intelligent models to draw inferences. Each chapter starts with the importance, problem statement, and motivation. A description of the proposed methodology is provided, and related works are also presented. Each chapter can be read independently, and therefore, the book is a valuable resource for researchers, health professionals, postgraduate students, postdoc researchers, and academicians in the fields of BCI, prosthesis, computer vision, and mental state estimation, and all those who wish to broaden their knowledge in the allied field.

Focuses on the advancements, challenges, and prospects for future technologies over noninvasive brain computer interfaces (BCIs), including the processing and analysis of multimodal signals, integrated calculation-acquisition devices, and implantable technologies.Presents theories, algorithms, realizations, applications, approaches, and challenges that will have their impact and contribution in the design and development of modern and effective BCIs.Assists in understanding the predominance of BCI technology in various applications.

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

Artificial Intelligence Strategies for Early Intervention in Neurodegeneration addresses the challenges surrounding the implementation of AI-based diagnoses of neurological disorders. These challenges include the lack of large, high-quality datasets, the necessity for standardization of data collection and analysis protocols, technical hurdles in developing accurate and reliable AI algorithms, and the requirement for regulatory approval and integration into clinical workflows. The book's content provides guidance to researchers on how to develop and integrate AI algorithms and biomarker analysis into their workflow, leading to a significant change in disease diagnosis.These techniques involve the analysis of physiological signals and images to identify patterns associated with specific diseases, and how AI algorithms can analyze medical imagery and movement and speech patterns to identify early signs of neurodegenerative diseases.

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future.The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become ‘black-box’ to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future.The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become ‘black-box’ to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

An unfortunate outcome of the growth of the Internet and mobile technologies has been the challenge of countering cybercrime. This book introduces and explains the latest trends and techniques of edge artificial intelligence (EdgeAI) intended to help cyber security experts design robust cyber defense systems (CDS), including host-based and network-based intrusion detection system and digital forensic intelligence. This book discusses the direct confluence of EdgeAI with big data, as well as demonstrating detailed reviews of recent cyber threats and their countermeasure. It provides computational intelligence techniques and automated reasoning models capable of fast training and timely data processing of cyber security big data, in addition to other basic information related to network security. In addition, it provides a brief overview of modern cyber security threats and outlines the advantages of using EdgeAI to counter these threats, as well as exploring various cyber defense mechanisms (CDM) based on detection type and approaches. Specific challenging areas pertaining to cyber defense through EdgeAI, such as improving digital forensic intelligence, proactive and adaptive defense of network infrastructure, and bio-inspired CDM, are also discussed. This book is intended as a reference for academics and students in the field of network and cybersecurity, particularly on the topics of intrusion detection systems, smart grid, EdgeAI, and bio-inspired cyber defense principles. The front-line EdgeAI techniques discussed will also be of use to cybersecurity engineers in their work enhancing cyber defense systems.

An unfortunate outcome of the growth of the Internet and mobile technologies has been the challenge of countering cybercrime. This book introduces and explains the latest trends and techniques of edge artificial intelligence (EdgeAI) intended to help cyber security experts design robust cyber defense systems (CDS), including host-based and network-based intrusion detection system and digital forensic intelligence. This book discusses the direct confluence of EdgeAI with big data, as well as demonstrating detailed reviews of recent cyber threats and their countermeasure. It provides computational intelligence techniques and automated reasoning models capable of fast training and timely data processing of cyber security big data, in addition to other basic information related to network security. In addition, it provides a brief overview of modern cyber security threats and outlines the advantages of using EdgeAI to counter these threats, as well as exploring various cyber defense mechanisms (CDM) based on detection type and approaches. Specific challenging areas pertaining to cyber defense through EdgeAI, such as improving digital forensic intelligence, proactive and adaptive defense of network infrastructure, and bio-inspired CDM, are also discussed. This book is intended as a reference for academics and students in the field of network and cybersecurity, particularly on the topics of intrusion detection systems, smart grid, EdgeAI, and bio-inspired cyber defense principles. The front-line EdgeAI techniques discussed will also be of use to cybersecurity engineers in their work enhancing cyber defense systems.

The text focuses on the application of artificial intelligence and machine learning techniques in Computing, solid-state electronic devices, and communication engineering.Investigates the role of smart technologies such as artificial intelligence, machine learning, and deep learning in the fabrication and manufacturing of solid-state electronic devices.Discusses artificial intelligence applications in the design of solid-state electronic devices, microwave engineering, and remote sensing.Focuses on artificial intelligence and machine learning applications in designing miniaturized semiconductor integrated circuit chips, and modern microwave devices like microstrip antennas, and microstrip filters.Covers artificial intelligence and machine learning-based systems for mobile communication networks.Showcases applications of artificial intelligence for analog and mixed-signal circuits for mitigation of computational complexities.The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science, and engineering.

INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.

In recent years, new applications on computer-aided technologies for telemedicine have emerged. Furthermore, this volume includes comprehensive reviews describing procedures and techniques, which are crucial to support researchers in the field who want to replicate these methodologies in solving their related research problems.

In recent years, new applications on computer-aided technologies for telemedicine have emerged. Furthermore, this volume includes comprehensive reviews describing procedures and techniques, which are crucial to support researchers in the field who want to replicate these methodologies in solving their related research problems.

This book provides detail on applying Internet of Things (IoT) and Internet of Everything (IoE) in smart cities and their design aspects related to physical and network layer models.

This book provides detail on applying Internet of Things (IoT) and Internet of Everything (IoE) in smart cities and their design aspects related to physical and network layer models.

With rise of smart medical sensors, cloud computing and the health care technologies, “connected health” is getting remarkable consideration everywhere.

With rise of smart medical sensors, cloud computing and the health care technologies, “connected health” is getting remarkable consideration everywhere. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality. Cloud computing fits well in this scenario as it can provide high quality of clinical experience. Thus an IoT-cloud convergence can play a vital role in healthcare by offering better insight of heterogeneous healthcare content supporting quality care. It can also support powerful processing and storage facilities of huge data to provide automated decision making. This book aims to report quality research on recent advances towards IoT-Cloud convergence for smart healthcare, more specifically to the state-of-the-art approaches, design, development and innovative use of those convergence methods for providing insights into healthcare service demands. Students, researchers, and medical experts in the field of information technology, medicine, cloud computing, soft computing technologies, IoT and the related fields can benefit from this handbook in handling real-time challenges in healthcare. Current books are limited to focus either on soft computing algorithms or smart healthcare. Integration of smart and cloud computing models in healthcare resulting in connected health is explored in detail in this book.

This book experiences the future of patient-centered healthcare and dives into the latest advancements and transformative technologies that are revolutionizing the well-being of individuals around the globe. The readers can join authors on an engaging journey as the authors explore the captivating realm of ambient assisted living and unlock its immense potential for improving healthcare outcomes.This book goes beyond mere exploration; it invites readers to embark on a voyage of discovery as authors unveil the outcomes of groundbreaking research ideas. With a diverse range of applications, from deep learning in healthcare to cutting-edge models, the authors offer a comprehensive view of the opportunities and challenges that lie ahead.Whether you're a healthcare professional, an academic seeking the latest insights, or a researcher delving into the realms of ambient assistive technology, biomedical engineering, or computational intelligence, this book is an invaluable resource. Additionally, postgraduate students pursuing data engineering systems find it to be an essential guide.Each chapter stands independently, providing a comprehensive overview of problem formulation and its tangible outcomes. The readers can immerse themselves in the world of patient-centered healthcare today and become part of the forefront of innovation.

This book experiences the future of patient-centered healthcare and dives into the latest advancements and transformative technologies that are revolutionizing the well-being of individuals around the globe. The readers can join authors on an engaging journey as the authors explore the captivating realm of ambient assisted living and unlock its immense potential for improving healthcare outcomes.This book goes beyond mere exploration; it invites readers to embark on a voyage of discovery as authors unveil the outcomes of groundbreaking research ideas. With a diverse range of applications, from deep learning in healthcare to cutting-edge models, the authors offer a comprehensive view of the opportunities and challenges that lie ahead.Whether you're a healthcare professional, an academic seeking the latest insights, or a researcher delving into the realms of ambient assistive technology, biomedical engineering, or computational intelligence, this book is an invaluable resource. Additionally, postgraduate students pursuing data engineering systems find it to be an essential guide.Each chapter stands independently, providing a comprehensive overview of problem formulation and its tangible outcomes. The readers can immerse themselves in the world of patient-centered healthcare today and become part of the forefront of innovation.

This book provides a comprehensive overview of Human Activity Detection or Recognition (HADR) systems.

This book provides a comprehensive overview of Human Activity Detection or Recognition (HADR) systems.

This book focuses more on the transformative impact of person-centric health care, where it explores cutting-edge advancements in integrating artificial intelligence and machine learning to deliver personalized and efficient care. Key topics include the application of predictive models for critical health conditions such as brain stroke, lung cancer, diabetes, and Alzheimer's, as well as the integration of secure frameworks to protect sensitive patient data. The book also covers advanced techniques for recognizing human activities in ambient environments, optimizing patient data clustering, and evaluating deep learning methods for unique use cases like yoga pose classification and resource optimization in smart healthcare.Designed for healthcare professionals, researchers, data scientists, and technologists, this book presents a harmonious blend of technical insights and practical applications, emphasizing person-centric approaches. By focusing on multi-disease prediction, assistive technologies, and enhanced emergency management, this book serves as a vital resource for innovating healthcare delivery in smart environments.

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

This book highlights how optimized big data applications can be used for patient monitoring and clinical diagnosis. In fact, IoT-based applications are data-driven and mostly employ modern optimization techniques. The book also explores challenges, opportunities, and future research directions, discussing the stages of data collection and pre-processing, as well as the associated challenges and issues in data handling and setup.

The volume offers state-of-the-art chapters on energy management systems (EMS), renewable energy resources, micro-generation, green communications architectures and frameworks, green computing and education as well as energy-aware process optimization.