Build a strong and efficient IoT infrastructure at industrial and enterprise level by mastering Industrial IoT network Key FeaturesGain hands-on experience working with industrial architectureExplore the potential of cloud-based Industrial IoT platforms, analytics, and protocolsImprove business models and transform your workforce with Industry 4.0Book Description We live in an era where advanced automation is used to achieve accurate results. To set up an automation environment, you need to first configure a network that can be accessed anywhere and by any device. This book is a practical guide that helps you discover the technologies and use cases for Industrial Internet of Things (IIOT). Hands-On Industrial Internet of Things takes you through the implementation of industrial processes and specialized control devices and protocols. You’ll study the process of identifying and connecting to different industrial data sources gathered from different sensors. Furthermore, you’ll be able to connect these sensors to cloud network, such as AWS IoT, Azure IoT, Google IoT, and OEM IoT platforms, and extract data from the cloud to your devices. As you progress through the chapters, you’ll gain hands-on experience in using open source Node-Red, Kafka, Cassandra, and Python. You will also learn how to develop streaming and batch-based Machine Learning algorithms. By the end of this book, you will have mastered the features of Industry 4.0 and be able to build stronger, faster, and more reliable IoT infrastructure in your Industry. What you will learnExplore industrial processes, devices, and protocolsDesign and implement the I-IoT network flowGather and transfer industrial data in a secure wayGet to grips with popular cloud-based platformsUnderstand diagnostic analytics to answer critical workforce questionsDiscover the Edge device and understand Edge and Fog computingImplement equipment and process management to achieve business-specific goalsWho this book is for If you’re an IoT architect, developer, or stakeholder working with architectural aspects of Industrial Internet of Things, this book is for you.

This book focuses on the key technologies, challenges, and research directions of the Industrial Internet of Things (IIoT). It provides a basis for discussing open principles, methods, and research problems, and provides a systematic overview of the state-of-the-art research efforts, directions, and potential challenges associated with IIoT. Industrial Internet of Things: Technologies and Research Directions covers how industry automation is projected to be the largest and fastest-growing segment of the market. It explores the collaborative development of high-performance telecommunications, military, industrial, and general-purpose embedded computing applications, and offers a systematic overview of the state-of-the-art research efforts and new potential directions. Researchers, academicians, and professionals working in this inter-disciplinary area will be interested in this book.

Industrial IoT (IIoT) and Industry 4.0 are newly developing and fast emerging domains of interest among students, researchers, and professionals in academia and industry. Due to the popular demand of this topic, Introduction to Industrial Internet of Things and Industry 4.0 is written to serve a diverse readership from the domains of computer science and engineering, mechanical engineering, information technology, industrial engineering, electronics engineering, and other related branches of engineering. Based on the lead author’s massive open online courses (MOOCs), this book can be used as a textbook on the emerging paradigm of Industry 4.0 and IIoT, as well as a reference for professionals working in sectors of IIoT. The book covers the significant aspects of IIoT in detail, including sensors, actuators, data transmission, and data acquisition, which form the core of IIoT. Topics and concepts are presented in a comprehensive manner, so that readers can develop expertise and knowledge. The book helps beginners to gain a basic idea of Industry 4.0 and IIoT as the first section is an overview of IoT applications, infrastructure-based protocols, cloud computing, and fog computing. The second section is designed to impart a basic knowledge of Industry 4.0 and IIoT as well as of the different phases of development in industry. Delving into more advanced areas, other sections in the book cover: The business models and reference architecture of IIoT The technological aspects of Industry 4.0 and IIoT Predictive and prescriptive analytics applied in IIoT-based implementations Applications and case studies of IIoT Key enabling technologies of IIoT To aid students and professional master IIoT and Industry 4.0, the book includes conceptual questions, exercises, and learning objectives.

Industrial internet of things (IIoT) is changing the face of industry by completely redefining the way stakeholders, enterprises, and machines connect and interact with each other in the industrial digital ecosystem. Smart and connected factories, in which all the machinery transmits real-time data, enable industrial data analytics for improving operational efficiency, productivity, and industrial processes, thus creating new business opportunities, asset utilization, and connected services. IIoT leads factories to step out of legacy environments and arcane processes towards open digital industrial ecosystems. Innovations in the Industrial Internet of Things (IIoT) and Smart Factory is a pivotal reference source that discusses the development of models and algorithms for predictive control of industrial operations and focuses on optimization of industrial operational efficiency, rationalization, automation, and maintenance. While highlighting topics such as artificial intelligence, cyber security, and data collection, this book is ideally designed for engineers, manufacturers, industrialists, managers, IT consultants, practitioners, students, researchers, and industrial industry professionals.

Development in information and communication technologies has led to the advancement of business and enabled enterprises to produce on a global scale. Productivity is a key function in maintaining a competitive advantage in today’s market. The internet of things has rapidly become prevalent in the productivity efforts of businesses. Understanding these technologies and how to implement them into current business practices is vital for researchers and practitioners. Internet of Things (IoT) Applications for Enterprise Productivity is a collection of innovative research on the advancing methods productivity efforts of business through the implementation of the internet of things. While highlighting topics including employee motivation, enterprise productivity, and supply chain tracking, this book is ideally designed for manufacturing professionals, industrialists, engineers, managers, practitioners, academicians, and students seeking current research on enterprise production systems and its transformation using internet of things technologies.

This book develops the core system science needed to enable the development of a complex industrial internet of things/manufacturing cyber-physical systems (IIoT/M-CPS). Gathering contributions from leading experts in the field with years of experience in advancing manufacturing, it fosters a research community committed to advancing research and education in IIoT/M-CPS and to translating applicable science and technology into engineering practice. Presenting the current state of IIoT and the concept of cybermanufacturing, this book is at the nexus of research advances from the engineering and computer and information science domains. Readers will acquire the core system science needed to transform to cybermanufacturing that spans the full spectrum from ideation to physical realization.

This book has a focus on the development and deployment of the Industrial Internet of Things (IIoT) paradigm, discussing frameworks, methodologies, benefits and limitations, as well as providing case studies of employing the IoT vision in the industrial domain. IIoT is becoming an attractive business reality for many organisations such as manufacturing, logistics, oil and gas, energy and other utilities, mining, aviation, and many more. The opportunities for this paradigm are huge, and according to one report, the IIoT market is predicted to reach $125 billion by 2021. The driving philosophy behind the IIoT is that smart machines are better than humans at accurately capturing, analysing and communicating real-time data. The underlying technologies include distributed computing, machine learning, artificial intelligence, and machine-to-machine communication, with a typical IIoT system consisting of intelligent systems (applications, controllers, sensors, and security mechanisms), data communication infrastructure (cloud computing, edge computing, etc.), data analytics (to support business intelligence and corporate decision making), and most importantly the human element. The promised benefits of the IIoT include enhanced safety, better reliability, smart metering, inventory management, equipment tracking, and facilities management. There are, however, numerous issues that are also becoming the focus of active research, such as concerns regarding service availability, data security, and device communication. Lack of ubiquitous interoperability between heterogeneous devices is also a major concern. This book intends to fill a gap in the IIoT literature by providing the scientific contributions and latest developments from researchers and practitioners of international repute, focusing on frameworks, methodologies, benefits, and inherent issues/barriers to connected environments, especially in industrial settings. The intended audience includes network specialists, hardware engineers, and security experts who wish to adopt newer approaches for device connectivity, IoT security, and sensor-based devices design. University level students, researchers and practitioners will also find the latest innovation in technology and newer approaches relevant to the IIoT from a distributed computing perspective.