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.

This book provides a rough entry into the interdisciplinary field of "Infranomics." It enables better decision making in an increasing ambiguous, complex, emergent, interdependent, and uncertain world where we attempt to anticipate modern society trends and patterns in order to react appropriately. However, as with any emerging discipline, much research is needed at the applications and conceptual level. The applications level may require development and testing of methods, tools, and techniques to enable analysis and decision-making in ambiguous, complex, emergent, interdependent, and uncertain conditions while the conceptual level may require taping into driving philosophies, theories, and methodologies that form the basis for "Infranomics." Striking the right balance between applications and conceptual foundation (theory) requires rigorous research.

This book provides a springboard for robust discussions on applications, theory, and transformation of current thinking to better deal with modern society s problematic issues using "Infranomics.""

This book addresses a key issue in today's society: the safer transport of dangerous goods, taking into account people, the environment and economics. In particular, it offers a potential approach to identifying the issues, developing the models, providing the methods and recommending the tools to address the risks and vulnerabilities involved. We believe this can only be achieved by assessing those risks in a comprehensive, quantifiable and integrated manner. Examining both rail and road transportation, the book is divided into three sections, covering: the mature and accepted (by both academia and practitioners) methodology of risk assessment; the vulnerability assessment - a novel approach proposed as a vital complement to risk; guidance and support to build the tools that make methods and equations to yield: the Decision Support Systems. Throughout the book, the authors do not endeavor to provide THE solution. Instead, the book offers insightful food for thought for students, researchers, practitioners and policymakers alike.

This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring. Features: Provides a state-of-the-art computer vision application in the digital health care industry Reviews advances in computer vision and data science technologies for analyzing information on human function and disability Includes practical implementation of computer vision application using recent tools and software Explores computer vision-enabled medical/clinical data security in the cloud Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.

Enable Resilience-Informed Decision-Making with an insightful combination of systems engineering concepts In Gamification for Resilience: Informed Resilient Decision Making, a team of distinguished researchers delivers an insightful and exciting integration of game theory, design, and applications that explains how to create a resilient city that promotes sustainable development, well-being, and inclusive growth. The authors combine several concepts and techniques taken from serious gaming and integrate them into decision-making theory, demonstrating how to enable Resilience-Informed Decision-Making. The book addresses critical infrastructure systems and how to ensure these systems are supported against manmade and natural threats and hazards. It includes thought-provoking research questions and case applications that will engage and challenge readers and create an active and memorable learning experience. Readers will also find: A thorough introduction to systems theory as the basis for bridging science and the practice of engineering systems Comprehensive explorations of gamification and its application to the resilience-informed decision-making process Practical discussions of the analysis and assessment of risk and vulnerability via serious gaming Fulsome treatments of the representation of system complexity using object-oriented programming Perfect for professionals and researchers working in the areas of decision making, gamification, resilience, risk assessments, and critical infrastructures, Gamification for Resilience: Informed Resilient Decision Making will also benefit undergraduate and graduate students studying urban planning, smart cities, and related subjects.

This book provides a first-of-its-kind approach for using blockchain to enhance resilience in disaster supply chain and logistics management, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources - these are elements of volatility, uncertainty, complexity, and ambiguity (VUCA) describing a dynamic environment that now form the "new norm" for many leaders. Blockchain-Enabled Resilience: An Integrated Approach for Disaster Supply Chain and Logistics Management analyzes the application of blockchain technology used to enable resilience in a disaster supply chain network. It discusses IoT and DVFS algorithms for developing a network-based simulation and presents advancements in disaster supply chain strategies using smart contacts for collaborations. The book covers how success is based on collaboration, coordination, sovereignty, and equality in distributing resources and offers a theoretical analysis that reveals that enhancing resilience can improve collaboration and communication and can result in more time-efficient processing for disaster supply management. This book provides a first-of-its-kind approach for managers and policy-makers as well as researchers interested in using blockchain to enhance resilience in disaster supply chains, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources. Practical guidance is provided for managers interested in implementation. A robust research agenda is also provided for those interested in expanding present research.

This book addresses a key issue in today's society: the safer transport of dangerous goods, taking into account people, the environment and economics. In particular, it offers a potential approach to identifying the issues, developing the models, providing the methods and recommending the tools to address the risks and vulnerabilities involved. We believe this can only be achieved by assessing those risks in a comprehensive, quantifiable and integrated manner. Examining both rail and road transportation, the book is divided into three sections, covering: the mature and accepted (by both academia and practitioners) methodology of risk assessment; the vulnerability assessment - a novel approach proposed as a vital complement to risk; guidance and support to build the tools that make methods and equations to yield: the Decision Support Systems. Throughout the book, the authors do not endeavor to provide THE solution. Instead, the book offers insightful food for thought for students, researchers, practitioners and policymakers alike.

This book provides a rough entry into the interdisciplinary field of Infranomics. It enables better decision making in an increasing ambiguous, complex, emergent, interdependent, and uncertain world where we attempt to anticipate modern society trends and patterns in order to react appropriately. However, as with any emerging discipline, much research is needed at the applications and conceptual level. The applications level may require development and testing of methods, tools, and techniques to enable analysis and decision-making in ambiguous, complex, emergent, interdependent, and uncertain conditions while the conceptual level may require taping into driving philosophies, theories, and methodologies that form the basis for Infranomics. Striking the right balance between applications and conceptual foundation (theory) requires rigorous research. This book provides a springboard for robust discussions on applications, theory, and transformation of current thinking to better deal with modern society’s problematic issues using Infranomics.

This book explores Complex System Governance (CSG)—an emerging field concerned with the design, execution, and evolution of essential functions necessary to ensure continued viability of a system. The book focuses on three primary development areas to better understand and utilize current developments CSG. First, the conceptual foundations for CSG are developed, from systems theory, management cybernetics, and governance. Second, a set of critical CSG topics are examined from conceptual as well as practice perspectives. Third, several development and application issues are discussed. Ultimately, CSG is positioned as an emerging field with strong theoretical grounding and significant implications for improving practices and performance to better address complex systems and their problems.   

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.