Demystifying Federated Learning For Blockchain And Industrial Internet Of Things

In recent years, mobile technology and the internet of objects have been used in mobile networks to meet new technical demands. Emerging needs have centered on data storage, computation, and low latency management in potentially smart cities, transport, smart grids, and a wide number of sustainable environments. Federated learning’s contributions include an effective framework to improve network security in heterogeneous industrial internet of things (IIoT) environments. Demystifying Federated Learning for Blockchain and Industrial Internet of Things rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. It provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication. Covering topics such as smart agriculture, object identification, and educational big data, this premier reference source is an essential resource for computer scientists, programmers, government officials, business leaders and managers, students and faculty of higher education, researchers, and academicians.

As social robots and the artificial intelligence (AI) that powers them become more advanced, they will likely take on more social and work roles. There is a variety of ways social robots can be engaged in human life, and they can leave an impact in terms of ease of use, productivity, and human support. The interactivity and receptivity of social robots can encourage humans to form social relationships with them. But now robots are intended to perform socially intelligent and interactive services like reception, guidance, emotional companionship, and more, which makes social human-robot interaction essential to help improve aspects of quality of life as well as to improve the efficiency of human care services. AI-Enabled Social Robotics in Human Care Services addresses recent advances in the latest technologies, new research results, and developments in the area of social robotics and AI and the latest developments in the field and future directions that can be beneficial to human society and human care services. Covering topics such as agriculture waste management systems, elder care, and facial emotion recognition, this premier reference source is an essential resource for AI professionals, computer scientists, robotics engineers, human care professionals, students and educators of higher education, librarians, researchers, and academicians.

This book introduces recent wireless technologies and their impact on recent trends, applications, and opportunities. It explores the latest 6G, IoT, and Blockchain techniques with AI and evolutionary applications, showing how digital integration can be used to serve society. It explores the most important aspects of modern technologies, providing insights into the newest 6G technology and practices; covering the roles, responsibilities, and impact of IoT, 6G, and Blockchain practices to sustain the world economy. This book highlights the roles, responsibilities, and impact of IoT, 6G, and Blockchain and its practices. By describing the implementation strategies for Blockchain, IoT, and 6G, this book focuses on technologies related to the advancement in wireless ad-hoc networks and the current sustainability practices used in IoT. It offers popular use cases and case studies related to 6G, IoT, and Blockchain to provide a better understanding and covers the global approach towards the convergence of 6G, IoT, and Blockchain along with recent applications and future potential. The book is a reference for those working with 6G, IoT, AI, and its related application areas. Students at both the UG and PG levels in various departments such as manufacturing, electronics, telecommunications, computer science, other engineering fields, and information technology will be interested in this book. It is ideally designed for use by technology development, academicians, data scientists, industry professionals, researchers, and students.

The Internet of Things (IoT) is a widely distributed and networked system of interrelated and interacting computing devices and objects. Because of IoT’s broad scope, it presents unique security problems, ranging from unsecure devices to users vulnerable to hackers. Presenting cutting- edge research to meet these challenges, Internet of Things Vulnerabilities and Recovery Strategies presents models of attack on IoT systems and solutions to prevent such attacks. Examining the requirements to secure IoT- systems, the book offers recovery strategies and addresses security concerns related to: Data Routing Data Integrity Device Supervision IoT Integration Information Storage IoT Performance The book takes a holistic approach that encompasses visibility, segmentation, and protection. In addition to visual approaches and policy- driven measures, the book looks at developing secure and fault- tolerant IoT devices. It examines how to locate faults and presents mitigation strategies, as well as security models to prevent and thwart hacking. The book also examines security issues related to IoT systems and device maintenance.

FOG COMPUTING FOR INTELLIGENT CLOUD IOT SYSTEMS This book is a comprehensive guide on fog computing and how it facilitates computing, storage, and networking services Fog computing is a decentralized computing structure that connects data, devices, and the cloud. It is an extension of cloud computing and is an essential concept in IoT (Internet of Things), as it reduces the burden of processing in cloud computing. It brings intelligence and processing closer to where the data is created and transmitted to other sources. Fog computing has many benefits, such as reduced latency in processing data, better response time that helps the user’s experience, and security and privacy compliance that assures protecting the vital data in the cloud. It also reduces the cost of bandwidth, because the processing is achieved in the cloud, which reduces network bandwidth usage and increases efficiency as user devices share data in the local processing infrastructure rather than the cloud service. Fog computing has various applications across industries, such as agriculture and farming, the healthcare industry, smart cities, education, and entertainment. For example, in the agriculture industry, a very prominent example is the SWAMP project, which stands for Smart Water Management Platform. With fog computing’s help, SWAMP develops a precision-based smart irrigation system concept used in agriculture, minimizing water wastage. This book is divided into three sections. The first section studies fog computing and machine learning, covering fog computing architecture, application perspective, computational offloading in mobile cloud computing, intelligent Cloud-IoT systems, machine learning fundamentals, and data visualization. The second section focuses on applications and analytics, spanning various applications of fog computing, such as in healthcare, Industry 4.0, cancer cell detection systems, smart farming, and precision farming. This section also covers analytics in fog computing using big data and patient monitoring systems, and the emergence of fog computing concerning applications and potentialities in traditional and digital educational systems. Security aspects in fog computing through blockchain and IoT, and fine-grained access through attribute-based encryption for fog computing are also covered. Audience The book will be read by researchers and engineers in computer science, information technology, electronics, and communication specializing in machine learning, deep learning, the cyber world, IoT, and security systems.

The Internet of Things (IoT) and blockchain are two new technologies that combine elements in many ways. A system where the virtual and physical worlds interact is created by integrating pervasive computing, ubiquitous computing, communication technologies, sensing technologies, Internet Protocol, and embedded devices. A massive number of linked devices and vast amounts of data present new prospects for developing services that can directly benefit the economy, environment, society, and individual residents. Due to the size of IoT and insufficient data security, security breaches may have a huge impact and negative effects. IoT not only connects gadgets but also people and other entities, leaving every IoT component open to a wide variety of assaults. The implementation and application of IoT and blockchain technology in actual scientific, biomedical, and data applications are covered in this book. The book highlights important advancements in health science research and development by applying the distinctive capabilities inherent to distributed ledger systems. Each chapter describes the current uses of blockchain in real-world data collection, medicine development, device tracking, and more meaningful patient interaction. All of these are used to create opportunities for expanding health science research. This paradigm change is studied from the perspectives of pharmaceutical executives, biotechnology entrepreneurs, regulatory bodies, ethical review boards, and blockchain developers. Key Features: Provides a foundation for the implementation process of blockchain and IoT devices based on healthcare-related technology Image processing and IoT device researchers can correlate their work with other requirements of advanced technology in the healthcare domain Conveys the latest technology, including artificial intelligence and machine learning, in healthcare-related technology Useful for the researcher to explore new things like security, cryptography, and privacy in healthcare related technology Tailored for people who want to start in healthcare-related technology with blockchain and IoT This book is primarily for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, and biomedical engineering.

DEEP LEARNING TOOLS for PREDICTING STOCK MARKET MOVEMENTS The book provides a comprehensive overview of current research and developments in the field of deep learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of deep learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The book: details the development of an ensemble model for stock market prediction, combining long short-term memory and autoregressive integrated moving average; explains the rapid expansion of quantum computing technologies in financial systems; provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions; explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers. Audience The book has a wide audience of researchers in financial technology, financial software engineering, artificial intelligence, professional market investors, investment institutions, and asset management companies.