Joel J. P. C. Rodrigues - Böcker

Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others.• Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications• Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches• Discusses various techniques of IoT systems for healthcare data analytics• Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics• Focuses more on the application of algorithms in various real life biomedical and engineering problems

Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others.• Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications• Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches• Discusses various techniques of IoT systems for healthcare data analytics• Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics• Focuses more on the application of algorithms in various real life biomedical and engineering problems

This book discusses the applications and optimization of emerging smart technologies in the field of healthcare. It further explains different modeling scenarios of the latest technologies in the healthcare system and compares the results to better understand the nature and progress of diseases in the human body, which would ultimately lead to early diagnosis and better treatment and cure of diseases with the help of distributed technology. Covers the implementation models using technologies such as artificial intelligence, machine learning, and deep learning with distributed systems for better diagnosis and treatment of diseases. Gives in-depth review of technological advancements like advanced sensing technologies such as plasmonic sensors, usage of RFIDs, and electronic diagnostic tools in the field of healthcare engineering. Discusses possibilities of augmented reality and virtual reality interventions for providing unique solutions in medical science, clinical research, psychology, and neurological disorders. Highlights the future challenges and risks involved in the application of smart technologies such as cloud computing, fog computing, IOT, and distributed computing in healthcare. Confers to utilize the AI and ML and associated aids in healthcare sectors in the post-Covid 19 period to revitalize the medical setup.Contributions included in the book will motivate technological developers and researchers to develop new algorithms and protocols in the healthcare field. It will serve as a vast platform for gaining knowledge regarding healthcare delivery, health- care management, healthcare in governance, and health monitoring approaches using distributed environments. It will serve as an ideal reference text for graduate students and researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical fields.

This book discusses the applications and optimization of emerging smart technologies in the field of healthcare. It further explains different modeling scenarios of the latest technologies in the healthcare system and compares the results to better understand the nature and progress of diseases in the human body, which would ultimately lead to early diagnosis and better treatment and cure of diseases with the help of distributed technology. Covers the implementation models using technologies such as artificial intelligence, machine learning, and deep learning with distributed systems for better diagnosis and treatment of diseases. Gives in-depth review of technological advancements like advanced sensing technologies such as plasmonic sensors, usage of RFIDs, and electronic diagnostic tools in the field of healthcare engineering. Discusses possibilities of augmented reality and virtual reality interventions for providing unique solutions in medical science, clinical research, psychology, and neurological disorders. Highlights the future challenges and risks involved in the application of smart technologies such as cloud computing, fog computing, IOT, and distributed computing in healthcare. Confers to utilize the AI and ML and associated aids in healthcare sectors in the post-Covid 19 period to revitalize the medical setup.Contributions included in the book will motivate technological developers and researchers to develop new algorithms and protocols in the healthcare field. It will serve as a vast platform for gaining knowledge regarding healthcare delivery, health- care management, healthcare in governance, and health monitoring approaches using distributed environments. It will serve as an ideal reference text for graduate students and researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical fields.

This reference text addresses the importance of smart crop management for increasing yield and presents a framework for smart monitoring and regulation of crop observation. Further, it comprehensively covers important topics such as spatial decision support systems for precision farming, swarm intelligence in the optimal management of aquaculture farms, and intelligent harvesting algorithms for improving productivity.This book:• Presents meta-heuristic algorithms for optimization, economic crop planning, and use of effective water resource management.• Discusses spatial decision support systems for crop productivity management, watershed management, and precision farming.• Illustrates swarm intelligence-based optimization techniques, data mining, and machine learning methods for aquaculture operations.• Highlights artificial intelligence and machine learning-based harvesting algorithms for improving productivity.• Explains the use of green Internet of Things security solutions for agriculture, plant condition management, and greenhouse simulation.It is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, agricultural science, and information technology.

Artificial Intelligence in Healthcare for the Elderly provides valuable insights into how artificial intelligence can transform healthcare through personalized monitoring, ethical considerations, and real-world applications. Artificial intelligence has the potential to revolutionize healthcare for the elderly by providing efficient and personalized monitoring and care. Though this technology has the potential to revolutionize care, there is currently little information on the potential of this technology in elderly healthcare. Artificial Intelligence in Healthcare for the Elderly explores AI algorithms that can transform health monitoring for older adults by analyzing data from wearable devices, electronic health records, and other sources that provide real-time data analysis, detect early warning signs of diseases, and offer personalized treatment. This book addresses the critical ethical, societal, and practical aspects of elderly care that are often overlooked with insights from various disciplines, including healthcare, technology, ethics, and sociology, to offer a holistic perspective on AI’s impact on aging. Artificial Intelligence in Healthcare for the Elderly offers an all-encompassing perspective on AI technologies employed in elderly healthcare by examining the specific types of technology used and delineating its role in elderly healthcare, drawing insights from existing research and case studies.

Classical computers encode information in binary bits that can either be 0s or 1s. In a quantum computer, the basic unit of memory is a quantum bit or qubit. These qubits play a similar role in terms of storing information, but use physical systems, such as the spin of an electron or the orientation of a photon, to do so. In situations where there are a large number of possible feature combinations, quantum computers can consider them simultaneously, speeding up the data processing time.In healthcare, where there are often large numbers of possible factors to consider, quantum computers can address them simultaneously, thereby allowing doctors to compare much, much more data, and all permutations of that data, in parallel to discover the best patterns that describe it, and therefore predict the best treatment options.This edited book explores the field of quantum computing and machine learning for medical data processing, and is a useful resource for computer engineers, researchers, healthcare technologists and scientists specialising in quantum computing, quantum AI, data processing, deep learning, machine learning, smart healthcare, and medical data systems.

This book provides a sound theoretical base and an extensive practical expansion of smart sustainable cities and societies, while also examining case studies in the area to help readers understand IoT driven solutions in smart cities.

This book provides a sound theoretical base and an extensive practical expansion of smart sustainable cities and societies, while also examining case studies in the area to help readers understand IoT driven solutions in smart cities. The book covers fundamentals, applications, and challenges of IoT for sustainable smart cities and society. With a good understanding of IoT and smart cities, and the associated communication protocols, the book provides an insight into its applications in several areas of smart cities. Models, architectures, and algorithms are presented that provide additional solutions. The main challenges discussed that are associated with IoT involved include security, privacy, authenticity, etc. The book is relevant to researchers, academics, professionals, and students.

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.

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.

The two-volume set CCIS 2053 and 2054 constitutes the refereed post-conference proceedings of the 13th International Advanced Computing Conference, IACC 2023, held in Kolhapur, India, during December 15–16, 2023.The 66 full papers and 6 short papers presented in these proceedings were carefully reviewed and selected from 425 submissions. The papers are organized in the following topical sections:Volume I:The AI renaissance: a new era of human-machine collaboration; application of recurrent neural network in natural language processing, AI content detection and time series data analysis; unveiling the next frontier of AI advancement.Volume II:Agricultural resilience and disaster management for sustainable harvest; disease and abnormalities detection using ML and IOT; application of deep learning in healthcare; cancer detection using AI.

The two-volume set CCIS 2053 and 2054 constitutes the refereed post-conference proceedings of the 13th International Advanced Computing Conference, IACC 2023, held in Kolhapur, India, during December 15–16, 2023.The 66 full papers and 6 short papers presented in these proceedings were carefully reviewed and selected from 425 submissions. The papers are organized in the following topical sections:Volume I:The AI renaissance: a new era of human-machine collaboration; application of recurrent neural network in natural language processing, AI content detection and time series data analysis; unveiling the next frontier of AI advancement.Volume II:Agricultural resilience and disaster management for sustainable harvest; disease and abnormalities detection using ML and IOT; application of deep learning in healthcare; cancer detection using AI.

As such, the proposed book serves as an indispensable resource for healthcare professionals, data scientists, researchers, and anyone invested in the future of healthcare and AI.

This book serves as a critical resource that bridges the gap between burgeoning technology and its practical implementation. The book starts with an in-depth exploration of healthcare 5.0 principles, laying the foundation for the reader to understand the current shifts in healthcare paradigms. Then, it dives into the intricacies of generative models in healthcare, detailing how these algorithms work and the applications they serve. The book further delves into the subsets of generative machine learning and deep learning techniques in healthcare. As we move towards more complex applications, the book takes a turn to address the critical subject of interpretability and explainability in generative models, a topic that resonates profoundly given the life-critical nature of medical decisions. Finally, the book concludes with a robust discussion on the security and privacy concerns that accompany the deployment of GAI in real healthcare settings. By offering a multidimensional viewpoint—coupled with case studies, statistical analyses, and expert insights—the book ensures that the reader is left with a nuanced understanding of how GAI can be both a boon and a challenge in healthcare. As such, the proposed book serves as an indispensable resource for healthcare professionals, data scientists, researchers, and anyone invested in the future of healthcare and AI.

This book features selected research papers presented at the First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019), organized by Northwest Group of Institutions, Punjab, India, Southern Federal University, Russia, and IAC Educational Trust, India along with KEC, Ghaziabad and ITS, College Ghaziabad as an academic partner and held on 12–13 October 2019. It includes innovative work from researchers, leading innovators and professionals in the area of communication and network technologies, advanced computing technologies, data analytics and intelligent learning, the latest electrical and electronics trends, and security and privacy issues.

This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies.

This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies.

This book features selected research papers presented at the Second International Conference on Computing, Communications, and Cyber-Security (IC4S 2020), organized in Krishna Engineering College (KEC), Ghaziabad, India, along with Academic Associates;

The book is aimed to foster knowledge based on Blockchain technology highlighting on the framework basics, operating principles and different incarnations. In addition, methods for inducing computational intelligence into existing blockchain frameworks thereby thwarting most of the limitations are also discussed.

The book is aimed to foster knowledge based on Blockchain technology highlighting on the framework basics, operating principles and different incarnations. In addition, methods for inducing computational intelligence into existing blockchain frameworks thereby thwarting most of the limitations are also discussed.

This book features selected research papers presented at the Third International Conference on Computing, Communications, and Cyber-Security (IC4S 2021), organized in Krishna Engineering College (KEC), Ghaziabad, India, along with Academic Associates;

This book provides a holistic and comprehensive approach to deep learning for vehicular ad hoc networks (VANETs), covering various aspects such as applications, agency involvement, and potential ethical and legal issues.

The book presents selected papers from the International Conference on Data Science and Communication (ICTDsC 2023) organized by the Department of Electronics and Communication Engineering and Department of Engineering Science and Humanities (DESH) Siliguri Institute of Technology, India during 23 – 24 March 2023 in Siliguri, India.