Smart Computing Applications

The new book "Smart Green Energy Production" explores the innovative surfaces and Intersections between Intelligent Algorithms and Green Energy Technologies to advance and enhance sustainable energy solutions. This comprehensive guide covers state-of-the-art and future-oriented computational strategies for optimizing or optimally controlling green energy production and managing carbon dioxide emissions. Key topics also include the application of smart hybrid quantum computing, the efficiency of swarm intelligence, the scalability of cloud computing, as well as analytical, heuristic and sophisticated optimization and controlling techniques. This book provides a detailed analysis of how these technologies can be leveraged to create more efficient, cost-effective, as well as human-, environmentally and life-friendly energy systems, offering readers a thorough understanding of the future of sustainable energy generation, induction, production and consumption.

Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.

This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profi table cloud manufacturing will be gathered to present advanced and specialized research in the selected area.

This book presents the emerging technologies of Industry 4.0. It describes the growing trend towards automation and data exchange in the manufacturing industry, with a focus on the internet of things (IoT), the industrial internet of things (IIoT), cyberphysical systems (CPS), smart factories, cloud computing, cognitive computing, and artificial intelligence.

This book covers the emerging applications of different computational and optimization techniques in order to achieve a sustainable agriculture. A sustainable agricultural management requires tools in providing integrated, area-specifi c, and interpreted prediction or forecasting and guidance in every aspect in agriculture.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.

Knowledge Management makes the management of information and resources within a commercial organization more effective. The contributions of this book investigate the applications of Knowledge Management in the upcoming era of Semantic Web, or Web 3.0, and the opportunities for reshaping and redesigning business strategies for more effective outcomes.

This book presents research on the state-of-the-art methods and applications. Security and privacy related issues of cloud are addressed with best practices and approaches for secure cloud computing, such as cloud ontology, blockchain, recommender systems, optimization strategies, data security, intelligent algorithms, defense mechanisms for mitigating DDoS attacks, potential communication algorithms in cloud based IoT, secure cloud solutions.

"Sustainability in Healthcare: Advances in mHealth AI and Robotics" explores sustainable methods in the healthcare industry, focusing on rural and community healthcare improvement, the use of robots for sustainability, and the implementation of AI in healthcare. It also explores additive manufacturing, mobile health, biomedical engineering, and telemedicine's role in healthcare sustainability management. The book also discusses the ethical concerns, environmental, social, and economic implications of sustainability in healthcare supply chain management and pandemic management.

The book "Digital Transformation in Healthcare 5.0: Metaverse, Nanorobots, and Machine Learning" is a comprehensive discussion of disruptive technologies and their applications in healthcare. The book starts with an overview of blockchain technology's impact on the healthcare sector, emphasizing its potential to improve data security and interoperability. The book also discusses the Metaverse's role in healthcare transformation, utilizing a blockchain method to improve patient care and medical practices. The book also　focuses on the interrelationships of Blockchain-Enabled Metaverse Healthcare Systems and Applications, highlighting innovative strategies.　It also introduces an Intraocular Pressure Monitoring System for Glaucoma Patients, demonstrating the integration of IoT and Machine Learning for improved care. The book winds up with a Machine Learning Approach to Voice Analysis in Parkinson's disease Diagnosis, demonstrating the potential of voice analysis as a non-invasive diagnostic tool.

"Digital Transformation in Healthcare 5.0: IoT, AI, and Digital Twin" provides a comprehensive overview of the integration of cutting-edge technology with healthcare, from the Fourth Industrial Revolution (4IR) to the introduction of IoT, AI, and Digital Twin technologies. This in-depth discussion of the digital revolution expanding the healthcare industry covers a wide range of topics, including digital disruption in healthcare delivery, the impact of 4IR and Health 4.0, e-health services and applications, virtual reality's impact on accessible healthcare delivery, digital twins and dietary health technologies, big data analytics in healthcare systems, machine learning models for cost-effective healthcare delivery systems, affordable healthcare with machine learning, enhanced biomedical signal processing with machine learning, and data-driven AI for information retrieval of biomedical images.