Ashish Khanna – författare

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development.

Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems.

Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics

Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data. This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians.

The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in the healthcare sector is to come up with ways to provide personalized healthcare to patients by taking into account the enormous amounts of already existing data.

Provides case studies that illustrate the business processes underlying the use of big data and deep learning health analytics to improve health care delivery Supplies readers with a foundation for further specialized study in clinical analysis and data management Includes links to websites, videos, articles and other online content to expand and support the primary learning objectives for each major section of the book

Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The volume discusses not only positive findings, but also negative ones obtained by deep learning techniques, including the use of newly developed deep learning techniques rarely reported in the existing literature. The book excludes research works with ready data sets and includes only unique data use to better understand the state of deep learning in real-world cases, along with the feedback and user experiences from physicians and medical staff for applied deep learning-based solutions. Other applications presented in the book include hybrid solutions with deep learning support, disease diagnosis with deep learning focusing on rare diseases and cancer, patient care and treatment, genomics research, as well as research on robotics and autonomous systems.

Introduces deep learning, demonstrating concepts for a wide variety of medical applications using unique data, excluding research with ready datasets Encompasses a wide variety of biomedical applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing and disease diagnosis Provides a robust set of methods that will help readers appropriately and judiciously use the most suitable deep learning techniques for their applications

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation.

Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions

Wearable Telemedicine Technology for the Healthcare Industry: Product Design and Development focuses on recent advances and benefits of wearable telemedicine techniques for remote health monitoring and prevention of chronic conditions, providing real time feedback and help with rehabilitation and biomedical applications. Readers will learn about various techniques used by software engineers, computer scientists and biomedical engineers to apply intelligent systems, artificial intelligence, machine learning, virtual reality and augmented reality to gather, transmit, analyze and deliver real-time clinical and biological data to clinicians, patients and researchers.

Wearable telemedicine technology is currently establishing its place with large-scale impact in many healthcare sectors because information about patient health conditions can be gathered anytime and anywhere outside of traditional clinical settings, hence saving time, money and even lives.

Provides readers with methods and applications for wearable devices for ubiquitous health and activity monitoring, wearable biosensors, wearable app development and management using machine learning techniques, and more Integrates coverage of a number of key wearable technologies, such as ubiquitous textile systems for movement disorders, remote surgery using telemedicine, intelligent computing algorithms for smart wearable healthcare devices, blockchain, and more Provides readers with in-depth coverage of wearable product design and development

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including the wide variety of impacts the virus is having on societies and medical practice Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics

Sustainable Entrepreneurship is nowadays considered as a discipline at the cross-roads of many others. This book describes recent cases, techniques and tools proposed for leaders, entrepreneurs, and practitioners who are involved and responsible for making strategic decisions in their companies and aiming at sustainable development. This book highlights the use of new business models/methods that can be employed by organizations and researchers to save millions of dollars, to enhance the economic growth, as well as to resolve environmental and social issues, via sustainable networks, renewal energy distribution, and social/green entrepreneurship. It will provide a comprehensive discussion of practical techniques, like Machine Learning, Robotics, Photovoltaic solar energy, in the field of renewable energy, and other digital tools, such as digital marketing, crowdsourcing platforms, and digital currency. Meanwhile, it will enlighten the way for entrepreneurs and decision makers by helping them to learn how to grow their business. The focus will be on how to benefit from these techniques to develop sustainable and renewable energy-based projects, as well as digitalized new ventures. The book walks the reader through the latest emerging trends in digitalization that can support practitioners, managers, entrepreneurs, and researchers to help them appreciate the application of sustainable solutions in various functional domains.

Sustainable Entrepreneurship is nowadays considered as a discipline at the cross-roads of many others. This book describes recent cases, techniques and tools proposed for leaders, entrepreneurs, and practitioners who are involved and responsible for making strategic decisions in their companies and aiming at sustainable development. This book highlights the use of new business models/methods that can be employed by organizations and researchers to save millions of dollars, to enhance the economic growth, as well as to resolve environmental and social issues, via sustainable networks, renewal energy distribution, and social/green entrepreneurship. It will provide a comprehensive discussion of practical techniques, like Machine Learning, Robotics, Photovoltaic solar energy, in the field of renewable energy, and other digital tools, such as digital marketing, crowdsourcing platforms, and digital currency. Meanwhile, it will enlighten the way for entrepreneurs and decision makers by helping them to learn how to grow their business. The focus will be on how to benefit from these techniques to develop sustainable and renewable energy-based projects, as well as digitalized new ventures. The book walks the reader through the latest emerging trends in digitalization that can support practitioners, managers, entrepreneurs, and researchers to help them appreciate the application of sustainable solutions in various functional domains.

New prospects for biomedical and healthcare engineering are being created by the rapid development of Robotic and Artificial Intelligence techniques. Innovative technologies such as Artificial Intelligence, Deep Learning, Robotics, and IoT are currently under huge influence in today’s modern world. For instance, a micro-nano robot allows us to study the fundamental problems at a cellular scale owing to its precise positioning and manipulation ability; the medical robot paves a new way for the low-invasive and high-efficient clinical operation, and rehabilitation robotics is able to improve the rehabilitative efficacy of patients. This book aims at exhibiting the latest research achievements, findings, and ideas in the field of robotics in biomedical and healthcare engineering, primarily focusing on the walking assistive robot, telerobotic surgery, upper/lower limb rehabilitation, and radiosurgery. As a result, a wide range of robots are being developed to serve a variety of roles within the medical environment. Robots specializing in human treatment include surgical robots and rehabilitation robots. The field of assistive and therapeutic robotic devices is also expanding rapidly. These include robots that help patients rehabilitate from severe conditions like strokes, empathic robots that assist in the care of older or physically/mentally challenged individuals, and industrial robots that take on a variety of routine tasks, such as sterilizing rooms and delivering medical supplies and equipment, including medications. The objectives of the book are in terms of advancing the state-of-the-art of robotic techniques and addressing the challenging problems in biomedical and healthcare engineering. This book Lays a good foundation for the core concepts and principles of robotics in biomedical and healthcare engineering, walking the reader through the fundamental ideas with expert ease. Progresses on the topics in a step-by-step manner and reinforces theory with a full-fledged pedagogy designed to enhance students’ understanding and offer them a practical insight into the applications of it. Features chapters that introduce and cover novel ideas in healthcare engineering like Applications of Robots in Surgery, Microrobots and Nanorobots in Healthcare Practices, Intelligent Walker for Posture Monitoring, AI-Powered Robots in Biomedical and Hybrid Intelligent Systems for Medical Diagnosis, and so on.Deepak Gupta is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.Moolchand Sharma is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.Vikas Chaudhary is a Professor at the JIMS Engineering Management Technical Campus, GGSIPU, Greater Noida, India.Ashish Khanna currently works at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.

New prospects for biomedical and healthcare engineering are being created by the rapid development of Robotic and Artificial Intelligence techniques. Innovative technologies such as Artificial Intelligence, Deep Learning, Robotics, and IoT are currently under huge influence in today’s modern world. For instance, a micro-nano robot allows us to study the fundamental problems at a cellular scale owing to its precise positioning and manipulation ability; the medical robot paves a new way for the low-invasive and high-efficient clinical operation, and rehabilitation robotics is able to improve the rehabilitative efficacy of patients. This book aims at exhibiting the latest research achievements, findings, and ideas in the field of robotics in biomedical and healthcare engineering, primarily focusing on the walking assistive robot, telerobotic surgery, upper/lower limb rehabilitation, and radiosurgery. As a result, a wide range of robots are being developed to serve a variety of roles within the medical environment. Robots specializing in human treatment include surgical robots and rehabilitation robots. The field of assistive and therapeutic robotic devices is also expanding rapidly. These include robots that help patients rehabilitate from severe conditions like strokes, empathic robots that assist in the care of older or physically/mentally challenged individuals, and industrial robots that take on a variety of routine tasks, such as sterilizing rooms and delivering medical supplies and equipment, including medications. The objectives of the book are in terms of advancing the state-of-the-art of robotic techniques and addressing the challenging problems in biomedical and healthcare engineering. This book Lays a good foundation for the core concepts and principles of robotics in biomedical and healthcare engineering, walking the reader through the fundamental ideas with expert ease. Progresses on the topics in a step-by-step manner and reinforces theory with a full-fledged pedagogy designed to enhance students’ understanding and offer them a practical insight into the applications of it. Features chapters that introduce and cover novel ideas in healthcare engineering like Applications of Robots in Surgery, Microrobots and Nanorobots in Healthcare Practices, Intelligent Walker for Posture Monitoring, AI-Powered Robots in Biomedical and Hybrid Intelligent Systems for Medical Diagnosis, and so on.Deepak Gupta is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.Moolchand Sharma is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.Vikas Chaudhary is a Professor at the JIMS Engineering Management Technical Campus, GGSIPU, Greater Noida, India.Ashish Khanna currently works at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.

Intelligent Cyber-Physical Systems for Sustainable Healthcare addresses the integration of emerging technologies like Virtual Reality, Smart Robotics, and Human-Computer Interaction, which are crucial for maximizing digital health's potential. The book includes case studies that highlight challenges faced by medical practitioners and industry professionals, providing valuable insights for designing sustainable iCPS solutions. Aimed at biomedical engineers, researchers, and industry professionals, it offers guidance for developing practical applications in sustainable healthcare. Additionally, shared, cross-disciplinary experiences assist engineers with less clinical expertise in enhancing healthcare applications in the intelligent digital health sector. Overall, case studies illustrate past challenges in the healthcare industry and present effective solutions to overcome them, making the book a comprehensive resource for advancing sustainable healthcare practices.Focuses on the adoption of Intelligent Cyber-Physical Systems (iCPS) in Healthcare 4.0, emphasizing the integration of technologies such as Artificial Intelligence, Machine Learning, and the Internet of ThingsIncludes case studies to illustrate the challenges faced by practitioners and industry professionals, offering valuable lessons for the design and development of sustainable iCPSExplores how AI-driven iCPS, in conjunction with cloud resources, can analyze large volumes of healthcare data

AI-Driven Diagnostics for 6G-Enabled Smart Healthcare explores the transformative integration of artificial intelligence (AI) and next-generation 6G networks in the healthcare sector. The book begins by highlighting the evolution of healthcare technology and the critical role of AI-driven diagnostics, emphasizing how 6G facilitates real-time, ultra-reliable communication. Key features of 6G, such as ultra-low latency and massive connectivity are discussed, showcasing their impact on advanced healthcare applications like remote diagnostics and patient monitoring. In addition, the integration of AI in medical diagnostics is examined, focusing on machine learning and deep learning techniques that enhance disease detection through medical imaging and clinical data analysis.Users will also find content that explores the benefits of remote patient monitoring, particularly for underserved populations, and delves into edge AI for localized, low-latency diagnostic processing. Other sections cover real-time imaging diagnostics are highlighted and address predictive analytics, detailing AI models that forecast diseases and the role of IoT devices and wearables in healthcare diagnostics. Final sections cover ethical considerations and regulatory challenges.Combines artificial intelligence with next-generation 6G networks, addressing critical advancements in healthcare diagnosticsEmphasizes the capabilities of 6G in enabling ultra-low latency and high-speed data transfer, facilitating real-time decision-making in clinical settingsAddresses the ethical considerations and regulatory frameworks necessary for implementing AI diagnostics in a 6G-enabled environment, ensuring patient privacy and complianceIncludes real-world case studies that demonstrate the successful application of AI diagnostics over 6G networks, providing actionable insights and lessons learned for practitioners

As the world rapidly advances toward unparalleled connectivity and urbanization, the intersection of state-of-the-art telecommunications, smart city initiatives, and the Internet of Things (IoT) holds the potential for revolutionary changes in our daily lives. This book examines the complex interplay among these dynamic forces, analyzing the security challenges and opportunities that emerge as we venture into this technological frontier.Security Paradigms in 6G Smart Cities and IoT Ecosystems: Navigating the Future provides a comprehensive understanding of the security challenges and opportunities presented by integrating 6G networks, smart city initiatives, and IoT ecosystems. It equips readers with a look into emerging technological landscapes and offers practical insights, case studies, and best practices that can be directly applied to real-world scenarios, helping readers navigate challenges specific to their domains. The knowledge and strategies presented aim to implement robust security measures within 6G smart cities, IoT ecosystems, and advanced applications, safeguarding sensitive data and systems from potential threats. This book also explores the latest advancements in 6G networks, smart cities, and the Internet of Things (IoT), providing a deep understanding of how these technologies are shaping the future and it illustrates how to utilize emerging technologies such as blockchain, deep learning, and digital twin in a secure 6G-enabled smart city. By fostering collaboration and innovation, this book serves as a platform for a conversation among researchers, practitioners, policymakers, and industry professionals and aims to drive collective action in addressing security challenges and advancing the development of secure 6G smart cities and IoT ecosystems.By mastering the techniques outlined in this book, readers can gain a competitive edge in their respective fields, enabling them to develop innovative and secure solutions tailored to specific domains. Professionals in roles such as technical managers, data scientists, cybersecurity experts, and researchers can leverage the knowledge gained from this book to advance their careers and take on leadership roles in 6G smart cities and IoT projects within advanced contexts.

This book explores the convergence of artificial intelligence (AI) and the Internet of Things (IoT) in transforming healthcare delivery. It provides a comprehensive overview of AIoT healthcare systems, covering concepts, architectures, applications, challenges, and future directions.Transforming Healthcare with AI and IoT: Intelligent Solutions for a Digital Future delves into core AI and IoT concepts, it explores their integration in healthcare settings, and showcases real-world examples. Readers will gain valuable insights into how AI and IoT are already revolutionizing healthcare delivery, inspiring them with tangible examples of success. Through real-world case studies and practical insights, readers will learn how AI and IoT can optimize resource allocation, improve patient outcomes, and enhance overall system sustainability. It covers topics including big data analytics, personalized medicine, smart hospitals, telehealth, and virtual care. The book also addresses ethical considerations, security concerns, and challenges in deploying AIoT healthcare systems.The book is primarily written for professionals and researchers involved in healthcare management, information technology, and AI. Additionally, undergraduate and graduate students studying healthcare technology, AI, or related fields would also find it invaluable.

There are intrinsic vulnerabilities in traditional computer vision systems, such as data tampering and adversarial attacks. This book illustrates how blockchain's decentralized and immutable ledger can mitigate these risks. Further, it examines the role of proxy smart contracts in implementing security protocols and ensuring data integrity within computer vision approaches.Discusses the integration of emerging technologies such as blockchain and generative artificial intelligence for computer vision applications with service scenarios.Explores existing secure solutions for computer vision applications with blockchain and advanced technologies.Explains the fusion of Blockchain and machine learning techniques for intrusion detection in computer vision.Covers real-world computer vision applications, such as smart healthcare, smart parking, and smart education, with secure environments as case studies.Examines security and privacy challenges in computer vision applications, discussing mitigation procedures, regulatory frameworks, and ethical contemplations crucial for protecting individuals' rights.Blockchain and Artificial Intelligence for Secure Computer Vision Technologies and Applications is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer vision, artificial intelligence, and computer engineering.

This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.

AI-ENABLED 6G NETWORKS AND APPLICATIONS Provides authoritative guidance on utilizing AI techniques in 6G network design and optimization Written and edited by active researchers, this book covers hypotheses and practical considerations and provides insights into the design of evolutionary AI algorithms for 6G networks, with focus on network transparency, interpretability and simulatability for vehicular networks, space systems, surveillance systems and their usages in different emerging engineering fields. AI-Enabled 6G Networks and Applications includes a review of AI techniques for 6G Networks and will focus on deployment of AI techniques to efficiently and effectively optimize the network performance, including AI-empowered mobile edge computing, intelligent mobility and handover management, and smart spectrum management. This book includes the design of a set of evolutionary AI hybrid algorithms with communication protocols, showing how to use them in practice to solve problems relating to vehicular networks, aerial networks, and communication networks. Reviews various types of AI techniques such as AI-empowered mobile edge computing, intelligent handover management, and smart spectrum managementDescribes how AI techniques manage computation efficiency, algorithm robustness, hardware development, and energy managementIdentifies and provides solutions to problems in current 4G/5G networks and emergent 6G architecturesDiscusses privacy and security issues in IoT-enabled 6G NetworksExamines the use of machine learning to achieve closed-loop optimization and intelligent wireless communicationAI-Enabled 6G Networks and Applications is an essential reference guide to advanced hybrid computational intelligence methods for 6G supportive networks and protocols, suitable for graduate students and researchers in network forensics and optimization, computer science, and engineering.

This book addresses the difficult task of integrating computational techniques with virtual reality and healthcare. It discusses the use of virtual reality in various areas, such as healthcare, cognitive and behavioural training, understanding mathematical graphs, human–computer interaction, fluid dynamics in healthcare industries, accurate real-time simulation, and healthcare diagnostics.Presenting the computational techniques for virtual reality in healthcare, it is a valuable reference resource for professionals at educational institutes as well as researchers, scientists, engineers and practitioners in industry.

This book addresses the difficult task of integrating computational techniques with virtual reality and healthcare. It discusses the use of virtual reality in various areas, such as healthcare, cognitive and behavioural training, understanding mathematical graphs, human–computer interaction, fluid dynamics in healthcare industries, accurate real-time simulation, and healthcare diagnostics.Presenting the computational techniques for virtual reality in healthcare, it is a valuable reference resource for professionals at educational institutes as well as researchers, scientists, engineers and practitioners in industry.

Finally, a concise pocket guide designed as a quick reference for busy clinicians who seek to improve the care they provide to cancer patients and cancer survivors. Thankfully, advances in cancer care such as chemotherapy, radiation, and surgery mean that more people than ever before are surviving long after their cancer diagnosis.

This book brings together the latest research in smart sensors technology and exposes the reader to myriad industrial applications that this technology has enabled. The book emphasizes several topics in the area of smart sensors in industrial real-world applications. The contributions in this book give a broader view on the usage of smart sensor devices covering a wide range of interdisciplinary areas like Intelligent Transport Systems, Healthcare, Agriculture, Drone communications and Security.By presenting an insight into Smart Sensors for Industrial IoT, this book directs the readers to explore the utility and advancement in smart sensors and their applications into numerous research fields. Lastly, the book aims to reach through a mass number of industry experts, researchers, scientists, engineers, and practitioners and help them guide and evolve to advance research practices.

This book brings together the latest research in smart sensors technology and exposes the reader to myriad industrial applications that this technology has enabled. The book emphasizes several topics in the area of smart sensors in industrial real-world applications. The contributions in this book give a broader view on the usage of smart sensor devices covering a wide range of interdisciplinary areas like Intelligent Transport Systems, Healthcare, Agriculture, Drone communications and Security.By presenting an insight into Smart Sensors for Industrial IoT, this book directs the readers to explore the utility and advancement in smart sensors and their applications into numerous research fields. Lastly, the book aims to reach through a mass number of industry experts, researchers, scientists, engineers, and practitioners and help them guide and evolve to advance research practices.

This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community.

This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community.

This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control.The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design ofhybrid algorithms for applications in data analytics, classification model, and engineering control.

This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control.The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design ofhybrid algorithms for applications in data analytics, classification model, and engineering control.

This book presents the augmented reality (AR) and virtual reality (VR) automotive applications. augmented and virtual reality and uses the advantages of the latter to solve the problems faced by the former. Virtual and augmented reality presents a powerful engineering tool that finds application in various engineering fields.

This book presents the augmented reality (AR) and virtual reality (VR) automotive applications. augmented and virtual reality and uses the advantages of the latter to solve the problems faced by the former. Virtual and augmented reality presents a powerful engineering tool that finds application in various engineering fields.

Topics include health data analytics for cognitive IoT, usability evaluation of cognitive IoT for healthcare, interpretable cognitive IoT for health robotics, and wearables in the context of IoT for healthcare.