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The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected.
The Industrial Internet of Things (Industrial IoT--IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks' provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected.
The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0. Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving cars Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains Discusses important topics such as the Internet of robotic things, cloud robotics, and cognitive architecture for cyber-physical robotics Explains image compression, and advanced machine learning techniques for scientific programming in Industry 5.0 Presents a detailed discussion of smart manufacturing techniques, industrial Internet of things, and supply chain management in Industry 5.0 The text is primarily written for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, electrical engineering, production engineering, and mechanical engineering.
This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models.
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on Industrial IoT Technologies and Applications, IoT 2017, held in Wuhu, China, in March 2017. The volume contains 25 papers carefully reviewed and selected from 41 submissions focusing on topics such as big data, cloud computing, Internet of things, areas of control, mobile computing, and security.
This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Industrial IoT Technologies and Applications, IoT 2016, held in GuangZhou, China, in March 2016. The volume contains 26 papers carefully reviewed and selected from 55 submissions focusing on topics such as big data, cloud computing, Internet of Things (IoT).
Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach uses an innovative approach to explore how the Internet of Things (IoT) and big data can improve approaches, create efficiencies and make discoveries. Rapid growth of the IoT has encouraged many companies in the manufacturing sector to make use of this technology to unlock its potential. Pharmaceutical manufacturing companies are no exception to this, as IoT has the potential to revolutionize aspects of the pharmaceutical manufacturing process, from drug discovery to manufacturing. Using clear, concise language and real world case studies, this book discusses systems level from both a human-factors point-of-view and the perspective of networking, databases, privacy and anti-spoofing. The wide variety of topics presented offers readers multiple perspectives on a how to integrate the Internet of Things into pharmaceutical manufacturing. - Covers efficiency improvements of pharmaceutical manufacturing through IoT/Big Data approaches - Explores cutting-edge technologies through sensor enabled environment in the pharmaceutical industry - Discusses the systems level from both a human-factors point-of-view and the perspective of networking, databases, privacy and anti-spoofing
The aim of this handbook is to summarize the recent rapidly developed real-time computing technologies, from theories to applications. This handbook benefits the readers as a full and quick technical reference with a high-level historic review of technology, detailed technical descriptions and the latest practical applications. In general, the handbook is divided into three main parts (subjected to be modified): theory, design, and application covering different but not limited to the following topics: - Real-time operating systems - Real-time scheduling - Timing analysis - Programming languages and run-time systems - Middleware systems - Design and analysis tools - Real-time aspects of wireless sensor networks - Energy aware real-time methods
As technology continues to expand and develop, the internet of things (IoT) is playing a progressive role in the infrastructure of electronics. The increasing amount of IoT devices, however, has led to the emergence of significant privacy and security challenges. Security and Privacy Issues in Sensor Networks and IoT is a collection of innovative research on the methods and applications of protection disputes in the internet of things and other computing structures. While highlighting topics that include cyber defense, digital forensics, and intrusion detection, this book is ideally designed for security analysts, IT specialists, software developers, computer engineers, industry professionals, academicians, students, and researchers seeking current research on defense concerns in cyber physical systems.
This open access book introduces how to manage important tasks in industrial wireless networks. Important tasks must be completed on time and with guaranteed quality; that is the consensus reached by system designers and users. However, for too long, important tasks have often been given unnecessary urgency, and people intuitively believe that important tasks should be executed first so that their performance can be guaranteed. Actually, in most cases, their performance can be guaranteed even if they are executed later, and the “early” resources can be utilized for other, more urgent tasks. Therefore, confusing importance with urgency hinders the proper use of system resources. In 2007, mixed criticality was proposed to indicate that a system may contain tasks of various importance levels. Since then, system designers and users have distinguished between importance and urgency. In the industrial field, due to the harsh environment they operate in, industrial wireless networks’ quality of service (QoS) has always been a bottleneck restricting their applications. Therefore, this book introduces criticality to label important data, which is then allocated more transmission resources, ensuring that important data’s QoS requirements can be met to the extent possible. To help readers understand how to apply mixed-criticality data to industrial wireless networks, the content is divided into three parts. First, we introduce how to integrate the model of mixed-criticality data into industrial wireless networks. Second, we explain how to analyze the schedulability of mixed-criticality data under existing scheduling algorithms. Third, we present a range of novel scheduling algorithms for mixed-criticality data. If you want to improve the QoS of industrial wireless networks, this book is for you.