Download Free Enabling Next Generation Industrial Control Networks Book in PDF and EPUB Free Download. You can read online Enabling Next Generation Industrial Control Networks and write the review.

Future Trends and Challenges for ICT Standardization identifies the importance of ICT standardization for strengthening the Indian industrial and business sector through Global ICT Standardization Forum for India (GISFI-www.gisfi.org). It outlines the major challenges and trends in the ICT development worldwide while mapping the Indian efforts on the background of the overall progress. The technological areas covered are: - the need, importance, and management of radio spectrum, - the development of future radio access technologies, - the convergence of telecommunications and broadcasting, - the possibilities and challenges brought by the Internet of Things (IoT), - the environment sustainability through the use of Green ICT The motivation behind this book is to provide a more informed context to ensure sustainable scientific and economic growth. It puts forward the best research roadmaps, strategies, and challenges contributed by engineers from the industry, academia, and government, and it addresses the benefits to the entire society resulting from standardization.
This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas.
Manufacturing in Europe is under great pressure from structural changes in the global economy. The high technical, social and cultural standards in Europe mean that our manufacturing enterprises lead the world but inevitably production and consumption continues to migrate to regions that allow higher profitability from lower costs of production with the promise of new markets. Structural changes in European industries will influence employment and welfare. However, there are signs of a new High-Adding-Value industrial revolution. This book has the answers that will allow us to avoid the negative consequences of this migration. A new model of future manufacturing – ManuFuture - has been forged in discussion with the world’s leading scientists in manufacturing and many experts from research, industry and economic policy. The results of this, the road to competitive and sustainable manufacturing, are captured in this fundamental book. The generic Model of ManuFuture, a Vision 2020 and a Strategic Research Agenda and the proactive initiatives required are presented here. They show the approach to manufacturing in the age of knowledge and the actions that must be taken.
With the rise of mobile and wireless technologies, more sustainable networks are necessary to support communication. These next-generation networks can now be utilized to extend the growing era of the Internet of Things. Enabling Technologies and Architectures for Next-Generation Networking Capabilities is an essential reference source that explores the latest research and trends in large-scale 5G technologies deployment, software-defined networking, and other emerging network technologies. Featuring research on topics such as data management, heterogeneous networks, and spectrum sensing, this book is ideally designed for computer engineers, technology developers, network administrators and researchers, professionals, and graduate-level students seeking coverage on current and future network technologies.
This book presents cutting-edge emerging technologies and approaches in the areas of service-oriented architectures, intelligent devices and cloud-based cyber-physical systems. It provides a clear view on their applicability to the management and automation of manufacturing and process industries. It offers a holistic view of future industrial cyber-physical systems and their industrial usage and also depicts technologies and architectures as well as a migration approach and engineering tools based on these. By providing a careful balance between the theory and the practical aspects, this book has been authored by several experts from academia and industry, thereby offering a valuable understanding of the vision, the domain, the processes and the results of the research. It has several illustrations and tables to clearly exemplify the concepts and results examined in the text and these are supported by four real-life case-studies. We are witnessing rapid advances in the industrial automation, mainly driven by business needs towards agility and supported by new disruptive advances both on the software and hardware side, as well as the cross-fertilization of concepts and the amalgamation of information and communication technology-driven approaches in traditional industrial automation and control systems. This book is intended for technology managers, application designers, solution developers, engineers working in industry, as well as researchers, undergraduate and graduate students of industrial automation, industrial informatics and production engineering.
5G INNOVATIONS FOR INDUSTRY TRANSFORMATION Authoritative resource providing insight on real-life industrial 5G use cases in driving customer value, productivity, and sustainability ambitions With 5G innovations rapidly expanding to different areas within technology, 5G Innovations for Industry Transformation provides key information on how 5G technology can positively impact digital transformation in the industry sectors, discussing new data-driven business opportunities, including green digital transition, new standards for sustainability, and real-time data-driven services, introducing case studies that cover a variety of industries, from the oil & gas industry to the telecom industry, along with the lessons learned from these case studies, and providing insights into how 5G technology will transform businesses by sharing real-time customer solutions, fair data sharing principles, and ecosystem and change management. The book summarizes novelty aspects in a compact and practical way to benefit users and specialists in the field who want to understand some of the very key aspects of 5G. To aid in reader comprehension, the book contains tables, figures of technical principles and architectural block diagrams, and photographs further explaining key topics. Sample topics covered in 5G Innovations for Industry Transformation include: 5G SA technology with new capabilities, 5G private networks, and how smart, connected products are transforming competition Implications of 5G applied to your particular business and/or industry, and how to scale up and industrialize based on these implications How to lead the charge in relation to optimizing business practices based on the advent of 5G, and details on navigating the platform economy How 5G affects data privacy and security, and other integrated capabilities of 5G, such as processes, data, technology, and competencies Based on real-world experiences and high-quality research and presenting practical examples that serve as a useful guiding hand, 5G Innovations for Industry Transformation is an essential resource for change leaders, enterprise architects, and software developers of any industrial enterprise seeking to drive digitalization forward in their value chain and organization.
Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.