As the number of Internet of Things (IoT) elements grows exponentially, their interactions can generate a massive amount of raw and multi-structured data. The challenge with this data explosion is to transform any raw data into information and knowledge, which can be used by people and systems to make intelligent decisions. Industrial IoT Application Architectures and Use Cases explores how artificial intelligence (AI), data analytics, and IoT technology combine to promote intelligent decision-making and automation in a range of industries. With faster, more stable AI algorithms and approaches, knowledge discovery and dissemination from IoT-device data can be simplified and streamlined. An era of powerful cognitive technology is beginning due to cloud-based cognitive systems that are forming the foundation of game-changing intelligent applications. This book presents next-generation use cases of IoT and IoT data analytics for a variety of industrial verticals as given below: An Intelligent IoT framework for smart water management An IoT-enabled smart traffic control system for congestion control and smart traffic management An intelligent airport system for airport management and security surveillance An IoT framework for healthcare to integrate and report patient information Fuzzy scheduling with IoT for tracking and monitoring hotel assets An IoT system for designing drainage systems and monitoring drainage pipes Predictive maintenance of plant equipment to decide the actual mean time to malfunction Integrated neural networks and IoT systems for predictive equipment maintenance IoT integration in blockchain for smart waste management This book also includes a chapter on the IoT paradigm and an overview of uses cases for personal, social, and industrial applications.

As the number of Internet of Things (IoT) elements grows exponentially, their interactions can generate a massive amount of raw and multi-structured data. The challenge with this data explosion is to transform any raw data into information and knowledge, which can be used by people and systems to make intelligent decisions. Industrial IoT Application Architectures and Use Cases explores how artificial intelligence (AI), data analytics, and IoT technology combine to promote intelligent decision-making and automation in a range of industries. With faster, more stable AI algorithms and approaches, knowledge discovery and dissemination from IoT-device data can be simplified and streamlined. An era of powerful cognitive technology is beginning due to cloud-based cognitive systems that are forming the foundation of game-changing intelligent applications. This book presents next-generation use cases of IoT and IoT data analytics for a variety of industrial verticals as given below: An Intelligent IoT framework for smart water management An IoT-enabled smart traffic control system for congestion control and smart traffic management An intelligent airport system for airport management and security surveillance An IoT framework for healthcare to integrate and report patient information Fuzzy scheduling with IoT for tracking and monitoring hotel assets An IoT system for designing drainage systems and monitoring drainage pipes Predictive maintenance of plant equipment to decide the actual mean time to malfunction Integrated neural networks and IoT systems for predictive equipment maintenance IoT integration in blockchain for smart waste management This book also includes a chapter on the IoT paradigm and an overview of uses cases for personal, social, and industrial applications.

This book provides a detailed insight into Robotic Process Automation (RPA) technologies linked with AI that will help organizations implement Industry 4.0 procedures. RPA tools enhance their functionality by incorporating AI objectives, such as use of artificial neural network algorithms, text mining techniques, and natural language processing techniques for information extraction and the subsequent process of optimization and forecasting scenarios for the purpose of improving an organization's operational and business processes. The target readers of this book are researchers, professors, graduate students, scientists, policymakers, professionals, and developers working in the IT and ITeS sectors, i.e. people who are working on emerging technologies. This book also provides insights and decision support tools necessary for executives concerned with different industrial and organizational automation-centric jobs, knowledge dissemination, information, and policy development for automation in different educational, government, and non-government organizations. This book is of special interest to college and university educators who teach AI, machine learning, blockchain, business intelligence, cognitive intelligence, and brain intelligence courses in different capacities.

Blockchain technology presents numerous advantages that include increased transparency, reduced transaction costs, faster transaction settlement, automation of information, increased traceability, improved customer experience, improved digital identity, better cyber security, and user-controlled networks. These potential applications are widespread and diverse including funds transfer, smart contracts, e-voting, efficient supply chain, and more in nearly every sector of society including finance, healthcare, law, trade, real estate, and other important areas. However, there are challenges and limitations that exist such as high energy consumption, limited scalability, complexity, security, network size, lack of regulations, and other critical issues. Nevertheless, blockchain is an attractive technology and has much to offer to the modern-day industry. Industry Use Cases on Blockchain Technology Applications in IoT and the Financial Sector investigates blockchain technology’s adoption and effectiveness in multiple industries and for the internet of things (IoT)-based applications, presents use cases from industrial and financial sectors as well as from other transaction-based services, and fills a gap in this respect by extending the existing body of knowledge in the suggested field. While highlighting topics such as cybersecurity, use cases, and models for blockchain implementation, this book is ideal for business managers, financial accountants, practitioners, researchers, academicians, and students interested in blockchain technology’s role and implementation in IoT and the financial sector.

This book addresses topics related to the Internet of Things (IoT), machine learning, cyber-physical systems, cloud computing, and autonomous vehicles in Industry 4.0. It investigates challenges across multiple sectors and industries and considers Industry 4.0 for operations research and supply chain management. Cyber-Physical, IoT, and Autonomous Systems in Industry 4.0 encourages readers to develop novel theories and enrich their knowledge to foster sustainability. It examines the recent research trends and the future of cyber-physical systems, IoT, and autonomous systems as they relate to Industry 4.0. This book is intended for undergraduates, postgraduates, academics, researchers, and industry individuals to explore new ideas, techniques, and tools related to Industry 4.0.

This book reviews the convergence technologies like cloud computing, artificial intelligence (AI) and Internet of Things (IoT) in healthcare and how they can help all stakeholders in the healthcare sector. The book is a proficient guide on the relationship between AI, IoT and healthcare and gives examples into how IoT is changing all aspects of the healthcare industry. Topics include remote patient monitoring, the telemedicine ecosystem, pattern imaging analytics using AI, disease identification and diagnosis using AI, robotic surgery, prediction of epidemic outbreaks, and more. The contributors include applications and case studies across all areas of computational intelligence in healthcare data. The authors also include workflow in IoT-enabled healthcare technologies and explore privacy and security issues in healthcare-based IoT.

Go beyond connecting services to understand the unique challenges encountered in industrial environments by building Industrial IoT architectures using AWS Purchase of the print or kindle book includes a free eBook in the PDF format Key FeaturesUnderstand the key components of IoT Architecture and how it applies to Industry 4.0Walk through extensive examples and solutions across multiple IndustriesLearn how to collect, process, store, and analyse Industrial IoT dataBook Description When it comes to using the core and managed services available on AWS for making decisions about architectural environments for an enterprise, there are as many challenges as there are advantages. This Industrial IoT book follows the journey of data from the shop floor to the boardroom, identifying goals and aiding in strong architectural decision-making. You'll begin from the ground up, analyzing environment needs and understanding what is required from the captured data, applying industry standards and conventions throughout the process. This will help you realize why digital integration is crucial and how to approach an Industrial IoT project from a holistic perspective. As you advance, you'll delve into the operational technology realm and consider integration patterns with common industrial protocols for data gathering and analysis with direct connectivity to data through sensors or systems. The book will equip you with the essentials for designing industrial IoT architectures while also covering intelligence at the edge and creating a greater awareness of the role of machine learning and artificial intelligence in overcoming architectural challenges. By the end of this book, you'll be ready to apply IoT directly to the industry while adapting the concepts covered to implement AWS IoT technologies. What you will learnDiscover Industrial IoT best practices and conventionsUnderstand how to get started with edge computingDefine and build IoT solution architectures from scratchUse AWS as the core of your solution platformApply advanced analytics and machine learning to your dataDeploy edge processing to react in near real time to events within your environmentWho this book is for This book is for architects, engineers, developers, and technical professionals interested in building an edge and cloud-based Internet of Things ecosystem with a focus on industry solutions. Since the focus of this book is specifically on IoT, a solid understanding of core IoT technologies and how they work is necessary to get started. If you are someone with no hands-on experience, but are familiar with the subject, you'll find the use cases useful to learn how architectural decisions are made.

Translational bioinformatics (TBI) involves development of storage, analytics, and advanced computational methods to harvest knowledge from voluminous biomedical and genomic data into 4P healthcare (proactive, predictive, preventive, and participatory). Translational Bioinformatics Applications in Healthcare offers a detailed overview on concepts of TBI, biological and clinical databases, clinical informatics, and pertinent real-case applications. It further illustrates recent advancements, tools, techniques, and applications of TBI in healthcare, including Internet of Things (IoT) potential, toxin databases, medical image analysis and telemedicine applications, analytics of COVID-19 CT images, viroinformatics and viral diseases, and COVID-19–related research. Covers recent technologies such as Blockchain, IoT, and Big data analytics in bioinformatics Presents the role of translational bioinformatic methods in the field of viroinformatics, as well as in drug development and repurposing Includes translational healthcare and NGS for clinical applications Illustrates translational medicine systems and their applications in better healthcare Explores medical image analysis with focus on CT images and novel coronavirus disease detection Aimed at researchers and graduate students in computational biology, data mining and knowledge discovery, algorithms and complexity, and interdisciplinary fields of studies, including bioinformatics, health-informatics, biostatistics, biomedical engineering, and viroinformatics. Khalid Raza is an Assistant Professor, the Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi. His research interests include translational bioinformatics, computational intelligence methods and its applications in bioinformatics, viroinformatics, and health informatics. Nilanjan Dey is an Associate Professor, the Department of Computer Science and Engineering, JIS University, Kolkata, India. His research interests include medical imaging, machine learning, computer-aided diagnosis, and data mining.

SMART GRIDS AND INTERNET OF THINGS Smart grids and the Internet of Things (IoT) are rapidly changing and complicated subjects that are constantly changing and developing. This new volume addresses the current state-of-the-art concepts and technologies associated with the technologies and covers new ideas and emerging novel technologies and processes. Internet of Things (IoT) is a self-organized network that consists of sensors, software, and devices. The data is exchanged among them with the help of the internet. Smart Grids (SG) is a collection of devices deployed in larger areas to perform continuous monitoring and analysis in that region. It is responsible for balancing the flow of energy between the servers and consumers. SG also takes care of the transmission and distribution power to the components involved. The tracking of the devices present in SG is achieved by the IoT framework. Thus, assimilating IoT and SG will lead to developing solutions for many real-time problems. This exciting new volume covers all of these technologies, including the basic concepts and the problems and solutions involved with the practical applications in the real world. Whether for the veteran engineer or scientist, the student, or a manager or other technician working in the field, this volume is a must-have for any library. Smart Grids and Internet of Things: Presents Internet of Things (IoT) and smart grid (SG)-integrated frameworks along with their components and technologies Covers the challenges in energy harvesting and sustainable solutions for IoTSGs and their solutions for practical applications Describes and demystifies the privacy and security issues while processing data in IoTSG Includes case studies relating to IoTSG with cloud and fog computing machine learning and blockchain

Smart Home and Industrial IoT Devices: Critical Perspectives on Cyber Threats, Frameworks and Protocols provides an in-depth examination of the Internet of Things (IoT) and its profound impact on smart homes and industrial systems. The book begins by exploring the significance of IoT in smart homes, followed by an analysis of emerging cyber threats targeting smart homes and cyber-physical systems. It presents AI and machine learning-based frameworks for monitoring water quality and managing irrigation in agriculture, highlighting their role in IoT ecosystems. The text also discusses a framework to mitigate cyber-attacks on robotic systems and introduces a multinomial naive Bayesian classifier for analyzing smart IoT devices. Dataflow analysis and modeling experiments are detailed, along with a comparison of IoT communication protocols using anomaly detection and security assessment. The book concludes with a discussion on efficient, lightweight intrusion detection systems and a unique taxonomy for IoT frameworks. This book is ideal for students, researchers, and professionals seeking to understand and secure IoT environments.