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Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development.
Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.
Digital Twins for Smart Cities and Villages provides a holistic view of digital twin technology and how it can be deployed to develop smart cities and smart villages. Smart manufacturing, smart healthcare, smart education, smart agriculture, smart rural solutions, and related methodologies using digital twins are discussed, including challenges in deployment, their solutions and future roadmaps. This knowledge, enriched by a variety of case studies presented in the book, may empower readers with new capabilities for new research as well as new tasks and strategies for practical implementation and real-world problem solving.The book is thoughtfully structured, starting from the background of digital twin concepts and basic know-how to serve the needs of those new to the subject. It continues with implementation to facilitate and improve management in several urban contexts, infrastructures, and more. Global case study assessments further provide a deep characterization of the state-of-the-art in digital twin in urban and rural contexts. - Uniquely focuses on applications for smart cities and villages, including smart services for health, education, mobility, and agriculture - Provides use cases and practical deployment of research involved in the emerging uses of digital twins - Discusses all pertinent issues, challenges, and possible solutions instrumental in implementing digital twins smart solutions in this context - Edited and authored by a global team of experts in their given fields
This book comprehensively introduces readers to Digital Twins, from the basic concepts, core technologies and technical architecture, to application scenarios and other aspects. Readers will gain a profound understanding of the emerging discipline of Digital Twins. Covering the latest and cutting-edge application technologies of Digital Twins in various fields, the book offers practitioners concrete problem-solving strategies. At the same time, it helps those working in Digital Twins-related fields to deepen their understanding of the industry and enhance their professional knowledge and skills. Given its scope, the book can also be used as teaching material or a reference book for teachers and students of product design, industrial design, design management, design marketing and related disciplines at colleges and universities. Covering a variety of groundbreaking Digital Twins technologies, it can also provide new directions for researchers.
Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems. The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‐centric society of the future. New applications are increasingly reliant on machine‐to‐machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‐optimization for the task at hand while ensuring high dependability and ultra‐low latency. Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‐making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required. AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‐agent systems and network ultra‐broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.
This book covers the notion of the digital twin, which has the potential to alter the way systems are governed and manufactured. It also addresses the metaverse as an emerging technology with its roots in literature, cross-platform avatars, and artificial intelligence-oriented cybersecurity issues. The untapped potential of the metaverse and digital twins as enabling technologies for the next-generation industries is emphasized in various chapters. Digital twin technology enables manufacturers to comprehend their products throughout product design better, integrate simulation, tracking, and optimization in real-time, and appropriately analyze operations. Especially for complicated products or systems, testing on a digital twin is more efficient (more accessible, quicker, less error-prone, and less expensive). The product is examined in its virtual version before it is displayed in the actual world. Additionally, the digital twin minimizes operational expenses and increases the longevity of equipment and assets. By prolonging the life of the thing, they represent and enhance its working efficiency; it may minimize operating costs and prospective capital spending. The digital twin idea is becoming a reality as it has begun to be used in several industries, including energy, manufacturing, construction, transportation, aerospace, smart cities, healthcare, cyber security, finance, and agriculture. Academic and industrial experts highlighted the most compelling use cases of digital twins and metaverses and the challenges inherent in their implementation. Readers who want to make more effective systems will find the book useful. Also, people who want to get an idea and vision of how technology will change our lives will benefit from this book.
This book is neither a step-by-step guide nor a technical handbook. Instead, different insights for Engineers (especially Chief/Lead/Head/Principal) on the adoption of Digital Twins for physical counterparts in various sectors/industries such as Manufacturing, Building, Infrastructure, Oil & Gas, Healthcare, Energy, Telecommunication, and Transportation up to City levels. With the power of digital data upon various advanced technologies aligned with Industry 4.0 and surely better than traditional approaches, the Digital Twin is the way forward to smartly enhance performances, especially towards Sustainability. Because data is, to every Engineer, the key to making better-informed decisions about physical counterparts. Furthermore, Artificial Intelligence (AI) and Metaverse technologies are advancing to create more opportunities and excitement for Digital Twins. However, organizational commitment is a lot more important than focusing on specific advanced technologies in order to optimize the Return On Investment (ROI) and data security level of the Digital Twin adoption. With simple explanations and case studies, perhaps this book is actionable for Engineers to start adopting in their organization by starting small and later achieving better performances than before. Smart Plant, Smart Building, Smart Infrastructure, Smart City, and more from the Digital Twin adoption, in the long run, are absolutely the sustainable motivation behind it, economically, socially, and environmentally valuable.
This Open Access proceedings presents a good overview of the current research landscape of assembly, handling and industrial robotics. The objective of MHI Colloquium is the successful networking at both academic and management level. Thereby, the colloquium focuses an academic exchange at a high level in order to distribute the obtained research results, to determine synergy effects and trends, to connect the actors in person and in conclusion, to strengthen the research field as well as the MHI community. In addition, there is the possibility to become acquatined with the organizing institute. Primary audience is formed by members of the scientific society for assembly, handling and industrial robotics (WGMHI). The Editors Prof. Dr.-Ing. Thorsten Schüppstuhl is head of the Institute of Aircraft Production Technology (IFPT) at the Hamburg University of Technology. Prof. Dr.-Ing. Kirsten Tracht is head of the Bremen Institute for Mechanical Engineering (bime) at the University of Bremen. Prof. Dr.-Ing. Annika Raatz is head of the Institute of Assembly Technology (match) at the Leibniz University Hannover.
This book presents the role of AI-Driven Digital Twin in the Industry 4.0 ecosystem by focusing on Smart Manufacturing, sustainable development, and many other applications. It also discusses different case studies and presents an in-depth understanding of the benefits and limitations of using AI and Digital Twin for industrial developments. AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications introduces the role of Digital Twin in Smart Manufacturing and focuses on the Digital Twin framework throughout. It provides a summary of the various AI applications in the Industry 4.0 environment and emphasizes the role of advanced computational and communication technologies. The book offers demonstrative examples of AI-Driven Digital Twin in various application domains and includes AI techniques used to analyze the environmental impact of industrial operations along with examples. The book reviews the major challenges in the deployment of AI-Driven Digital Twin in the Industry 4.0 ecosystem and presents an understanding of how AI is used in the designing of Digital Twin for various applications. The book also enables familiarity with various industrial applications of computational and communication technologies and summarizes the ongoing research and innovations in the areas of AI, Digital Twin, and Smart Manufacturing while also tracking the various research challenges along with future advances. This reference book is a must-read and is very beneficial to students, researchers, academicians, industry experts, and professionals working in related fields.