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Cognitive Computing and Cyber Physical Systems: 4th EAI International Conference, IC4S 2023, Bhimavaram, Andhra Pradesh, India, August 4-6, 2023, Proceedings, Part I (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering #536)

by Prakash Pareek Nishu Gupta M. J. C. S. Reis

This 2-volume set constitutes the post-conference proceedings of the 4th EAI International Conference on Cognitive Computing and Cyber Physical Systems, IC4S 2023, Bhimavaram, Andhra Pradesh, India, during August 4-6, 2023. The theme of IC4S 2023 was: cognitive approaches with machine learning and advanced communications. The 70 full papers were carefully reviewed and selected from 165 submissions. The papers are clustered in thematical issues as follows: machine learning and its applications; cyber security and signal processing; image processing; smart power systems; smart city eco-system and communications.

Cognitive Computing and Information Processing: Third International Conference, CCIP 2017, Bengaluru, India, December 15-16, 2017, Revised Selected Papers (Communications in Computer and Information Science #801)

by T. N. Nagabhushan Prabhudev Jagadeesh Seema Shukla Chayadevi M. L. V. N. Aradhya

This book constitutes the refereed proceedings of the Third International Conference on Cognitive Computing and Information Processing, CCIP 2017, held in Bengaluru, India, in December 2017. The 43 revised full papers presented were carefully reviewed and selected from 130 submissions. The papers are organized in topical sections on cognitive computing in medical information processing; cognitive computing and its applications; cognitive computing in video analytics.

Cognitive Computing for Big Data Systems Over IoT: Frameworks, Tools and Applications (Lecture Notes on Data Engineering and Communications Technologies #14)

by Arun Kumar Sangaiah Arunkumar Thangavelu Venkatesan Meenakshi Sundaram

This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT). It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.

Cognitive Computing for Internet of Medical Things

by A. Prasanth, D. Lakshmi, Rajesh Kumar Dhanaraj, Balamurugan Balusamy, P.C. Sherimon

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT. Key Features Exploits the different prospects of cognitive computing techniques for the IoMT and smart healthcare applications Addresses the significance of IoMT and cognitive computing in the evolution of intelligent medical systems for biomedical applications Describes the different computing techniques of cognitive intelligent systems from a practical point of view: solving common life problems Explores the technologies and tools to utilize IoMT for the transformation and growth of healthcare systems Focuses on the economic, social, and environmental impact of IoMT-enabled smart healthcare systems This book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Cognitive Computing for Internet of Medical Things

by Sherimon P C A. Prasanth Lakshmi D Rajesh Kumar Dhanaraj Balamurugan Balusamy

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT. Key Features Exploits the different prospects of cognitive computing techniques for the IoMT and smart healthcare applications Addresses the significance of IoMT and cognitive computing in the evolution of intelligent medical systems for biomedical applications Describes the different computing techniques of cognitive intelligent systems from a practical point of view: solving common life problems Explores the technologies and tools to utilize IoMT for the transformation and growth of healthcare systems Focuses on the economic, social, and environmental impact of IoMT-enabled smart healthcare systems This book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Cognitive Computing for Machine Thinking (Innovations in Sustainable Technologies and Computing)

by Makarand R. Velankar Parikshit N. Mahalle Gitanjali R. Shinde

This book presents cognitive modeling along with the new paradigm machine thinking to enhance existing AI power and address its current limitations. This book provides overview of natural and artificial intelligence along with the computing models used currently. The need of advancing the current models is presented with suitable examples. The business case studies presented in different domains provide possible use of augmented intelligence with the proposed machine thinking paradigm. This book is targeted at academicians, researchers, students, professionals who belong to disciplines which involves intelligent computing and modelling human thinking. It provides possible multidisciplinary research directions including social psychology, artificial intelligence, HCI, cognition for applications in various domains.

Cognitive Computing for Risk Management (EAI/Springer Innovations in Communication and Computing)

by Sasmita Rani Samanta Pradeep Kumar Mallick Prasant Kumar Pattnaik Jnyana Ranjan Mohanty Zdzislaw Polkowski

This book presents applications of cognitive management and cognitive computing in the fields of risk management, cognitive fraud detection, and in business decision making. The book provides insights on how cognitive management and cognitive computing enable businesses to quickly augment human intelligence and help humans perform tasks better. For example, the authors describe how by analyzing patterns in big data, small data, and "dark data," cognitive technologies can detect human behavior and suggest options for personalizing of products and services. The book studies companies in industries such as automotive, airline, health care, retail, wealth management, and litigation who have adopted these approaches.Presents applications of cognitive computing and cognitive management used in augmenting and empowering business decisions;Shows how to employ the Internet of Things in businesses using a cognitive management framework;Discusses technical aspects and alternatives to traditional tools, algorithms, and methodologies in cognitive computing.

Cognitive Computing in Human Cognition: Perspectives and Applications (Learning and Analytics in Intelligent Systems #17)

by Pradeep Kumar Mallick Prasant Kumar Pattnaik Amiya Ranjan Panda Valentina Emilia Balas

This edited book designs the Cognitive Computing in Human Cognition to analyze to improve the efficiency of decision making by cognitive intelligence. The book is also intended to attract the audience who work in brain computing, deep learning, transportation, and solar cell energy. Due to this in the recent era, smart methods with human touch called as human cognition is adopted by many researchers in the field of information technology with the Cognitive Computing.

Cognitive Computing Models in Communication Systems (Smart and Sustainable Intelligent Systems)

by Budati Anil Kumar S. B. Goyal Sardar M. N. Islam

COGNITIVE COMPUTING MODELS IN COMMUNICATION SYSTEMS A concise book on the latest research focusing on problems and challenges in the areas of data transmission technology, computer algorithms, AI-based devices, computer technology, and their solutions. The book provides a comprehensive overview of state-of-the-art research work on cognitive models in communication systems and computing techniques. It also bridges the gap between various communication systems and solutions by providing the current models and computing techniques, their applications, the strengths and limitations of the existing methods, and the future directions in this area. The contributors showcase their latest research work focusing on the issues, challenges, and solutions in the field of data transmission techniques, computational algorithms, artificial intelligence (AI)-based devices, and computing techniques. Readers will find in this succinctly written and unique book: Topics covering the applications of advanced cognitive devices, models, architecture, and techniques. A range of case studies and applications that will provide readers with the tools to apply cutting-edge models and algorithms. In-depth information about new cognitive computing models and conceptual frameworks and their implementation. Audience The book is designed for researchers and electronics engineers, computer science engineers, industrial engineers, and mechanical engineers (both in academia and industry) working in the fields of machine learning, cognitive computing, mobile communication, and wireless network system.

Cognitive Computing Models in Communication Systems (Smart and Sustainable Intelligent Systems)

by Budati Anil Kumar S. B. Goyal Sardar M.N. Islam

COGNITIVE COMPUTING MODELS IN COMMUNICATION SYSTEMS A concise book on the latest research focusing on problems and challenges in the areas of data transmission technology, computer algorithms, AI-based devices, computer technology, and their solutions. The book provides a comprehensive overview of state-of-the-art research work on cognitive models in communication systems and computing techniques. It also bridges the gap between various communication systems and solutions by providing the current models and computing techniques, their applications, the strengths and limitations of the existing methods, and the future directions in this area. The contributors showcase their latest research work focusing on the issues, challenges, and solutions in the field of data transmission techniques, computational algorithms, artificial intelligence (AI)-based devices, and computing techniques. Readers will find in this succinctly written and unique book: Topics covering the applications of advanced cognitive devices, models, architecture, and techniques. A range of case studies and applications that will provide readers with the tools to apply cutting-edge models and algorithms. In-depth information about new cognitive computing models and conceptual frameworks and their implementation. Audience The book is designed for researchers and electronics engineers, computer science engineers, industrial engineers, and mechanical engineers (both in academia and industry) working in the fields of machine learning, cognitive computing, mobile communication, and wireless network system.

Cognitive Computing of Visual and Auditory Information (Reports of China’s Basic Research)

by Nanning Zheng

This book discusses fruitful achievements in basic cognitive theories, processing technologies of visual and auditory information and research platforms. This book also can provide strong support for the research and development of artificial intelligence of major national projects, playing important roles in national application systems such as unmanned systems and smart cities. In addition, it has laid a solid foundation for the development of artificial intelligence in China. Intended for researchers who have been following the evolution of and trends in the artificial intelligence, the book is also a valuable reference resource for practitioners and scholars at various levels and in various fields.

Cognitive Computing Recipes: Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow

by Adnan Masood Adnan Hashmi

Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday developers, by providing a combination of tools such as cognitive services APIs, machine learning platforms, and libraries.Along with an overview of the contemporary technology landscape, Machine Learning and Deep Learning with Cognitive Computing Recipes covers the business case for machine learning and deep learning. Covering topics such as digital assistants, computer vision, text analytics, speech, and robotics process automation this book offers a comprehensive toolkit that you can apply quickly and easily in your own projects. With its focus on Microsoft Cognitive Services offerings, you’ll see recipes using multiple different environments including TensowFlow and CNTK to give you a broader perspective of the deep learning ecosystem. What You Will LearnBuild production-ready solutions using Microsoft Cognitive Services APIsApply deep learning using TensorFlow and Microsoft Cognitive Toolkit (CNTK)Solve enterprise problems in natural language processing and computer vision Discover the machine learning development life cycle – from formal problem definition to deployment at scaleWho This Book Is ForSoftware engineers and enterprise architects who wish to understand machine learning and deep learning by building applications and solving real-world business problems.

Cognitive Computing Systems: Applications and Technological Advancements

by Vishal Jain

This new volume, Cognitive Computing Systems: Applications and Technological Advancements, explores the emerging area of artificial intelligence that encompasses machine self-learning, human-computer interaction, natural language processing, data mining and more. It introduces cognitive computing systems, highlights their key applications, discusses the technologies used in cognitive systems, and explains underlying models and architectures. Focusing on scientific work for real-world applications, each chapter presents the use of cognitive computing and machine learning in specific application areas. These include the use of speech recognition technology, application of neural networks in construction management, elevating competency in education, comprehensive health monitoring systems, predicting type 2 diabetes, applications for smart agricultural technology, human resource management, and more. With chapters from knowledgeable researchers in the area of artificial intelligence, cognitive computing, and allied areas, this book will be an asset for researchers, faculty, advances students, and industry professionals in many fields.

Cognitive Computing Systems: Applications and Technological Advancements

by Vishal Jain Akash Tayal Jaspreet Singh Arun Solanki

This new volume, Cognitive Computing Systems: Applications and Technological Advancements, explores the emerging area of artificial intelligence that encompasses machine self-learning, human-computer interaction, natural language processing, data mining and more. It introduces cognitive computing systems, highlights their key applications, discusses the technologies used in cognitive systems, and explains underlying models and architectures. Focusing on scientific work for real-world applications, each chapter presents the use of cognitive computing and machine learning in specific application areas. These include the use of speech recognition technology, application of neural networks in construction management, elevating competency in education, comprehensive health monitoring systems, predicting type 2 diabetes, applications for smart agricultural technology, human resource management, and more. With chapters from knowledgeable researchers in the area of artificial intelligence, cognitive computing, and allied areas, this book will be an asset for researchers, faculty, advances students, and industry professionals in many fields.

Cognitive Computing Using Green Technologies: Modeling Techniques and Applications (Green Engineering and Technology)

by Asis Kumar Tripathy

Cognitive Computing is a new topic which aims to simulate human thought processes using computers that self-learn through data mining, pattern recognition, and natural language processing. This book focuses on the applications of Cognitive Computing in areas like Robotics, Blockchain, Deep Learning, and Wireless Technologies. This book covers the basics of Green Computing, discusses Cognitive Science methodologies in Robotics, Computer Science, Wireless Networks, and Deep Learning. It goes on to present empirical data and research techniques, modelling techniques and offers a data-driven approach to decision making and problem solving. This book is written for researchers, academicians, undergraduate and graduate students, and industry persons who are working on current applications of Cognitive Computing.

Cognitive Computing Using Green Technologies: Modeling Techniques and Applications (Green Engineering and Technology)

by Asis Kumar Tripathy Chiranji Lal Chowdhary Mahasweta Sarkar Sanjaya Kumar Panda

Cognitive Computing is a new topic which aims to simulate human thought processes using computers that self-learn through data mining, pattern recognition, and natural language processing. This book focuses on the applications of Cognitive Computing in areas like Robotics, Blockchain, Deep Learning, and Wireless Technologies. This book covers the basics of Green Computing, discusses Cognitive Science methodologies in Robotics, Computer Science, Wireless Networks, and Deep Learning. It goes on to present empirical data and research techniques, modelling techniques and offers a data-driven approach to decision making and problem solving. This book is written for researchers, academicians, undergraduate and graduate students, and industry persons who are working on current applications of Cognitive Computing.

Cognitive Computing with IBM Watson: Build Smart Applications Using Artificial Intelligence As A Service

by Tanmay Bakshi

Cognitive computing is applicable to almost every industry, where humans engage in dialogue, ask questions, test ideas and make decisions. It enables us to use computers to recognize different types of human expression – literary, vocal, visual, and empathetic – which facilitates a deeper and scalable understanding of the problems that matter to us.

Cognitive Dependability Engineering: Managing Risks in Cyber-Physical-Social Systems under Deep Uncertainty

by Lech Bukowski

The work is a context-oriented analysis and synthesis of complex engineered systems to ensure continuous and safe operations under conditions of uncertainty. The book is divided in four parts, the first one comprises an overview of the development of systems engineering: starting with basics of Systems Science and Single Systems Engineering, through System of Systems Engineering to Cognitive Systems Engineering. The Cognitive Systems Engineering model was based on the concept of imperfect knowledge acquisition and management. The second part shows the evolutionary character of the dependability concept over the last fifty years. Beginning from simple models based on the classical probability theory, through the concepts of tolerating faults, as well as resilience engineering, we come to the assumptions of Cognitive Dependability Engineering (CDE), based on the concept of continuous smart operation, both under normal and abnormal conditions. The subject of the next part is analysis and synthesis of Cyber-Physical-Social (CPS) Systems. The methodology consists of the following steps: modeling CPS systems' structure, simulating their behavior in changing conditions and in situations of disruptions, and finally assessing the dependability of the entire system based on CDE. The last part of the work answers the question of how to deal with risks in CPS systems in situations of high level of uncertainty. The concept of a Cognitive Digital Twin was introduced to support the process of solving complex problems by experts, and on this basis a framework for cognitive dependability based problemsolving in CPS Systems operating under deep uncertainty was developed. The possibilities and purposefulness of using this framework have been demonstrated with three practical examples of disasters that have happened in the past and have been thoroughly analyzed.

Cognitive Dependability Engineering: Managing Risks in Cyber-Physical-Social Systems under Deep Uncertainty

by Lech Bukowski

The work is a context-oriented analysis and synthesis of complex engineered systems to ensure continuous and safe operations under conditions of uncertainty. The book is divided in four parts, the first one comprises an overview of the development of systems engineering: starting with basics of Systems Science and Single Systems Engineering, through System of Systems Engineering to Cognitive Systems Engineering. The Cognitive Systems Engineering model was based on the concept of imperfect knowledge acquisition and management. The second part shows the evolutionary character of the dependability concept over the last fifty years. Beginning from simple models based on the classical probability theory, through the concepts of tolerating faults, as well as resilience engineering, we come to the assumptions of Cognitive Dependability Engineering (CDE), based on the concept of continuous smart operation, both under normal and abnormal conditions. The subject of the next part is analysis and synthesis of Cyber-Physical-Social (CPS) Systems. The methodology consists of the following steps: modeling CPS systems' structure, simulating their behavior in changing conditions and in situations of disruptions, and finally assessing the dependability of the entire system based on CDE. The last part of the work answers the question of how to deal with risks in CPS systems in situations of high level of uncertainty. The concept of a Cognitive Digital Twin was introduced to support the process of solving complex problems by experts, and on this basis a framework for cognitive dependability based problemsolving in CPS Systems operating under deep uncertainty was developed. The possibilities and purposefulness of using this framework have been demonstrated with three practical examples of disasters that have happened in the past and have been thoroughly analyzed.

Cognitive Design for Artificial Minds

by Antonio Lieto

Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. Beginning with an overview of the historical, methodological and technical issues in the field of Cognitively-Inspired Artificial Intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realise biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biologically and cognitive accuracy of artificial systems in order project and predict their explanatory power with respect to the natural systems taken as source of inspiration. Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science.

Cognitive Design for Artificial Minds

by Antonio Lieto

Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. Beginning with an overview of the historical, methodological and technical issues in the field of Cognitively-Inspired Artificial Intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realise biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biologically and cognitive accuracy of artificial systems in order project and predict their explanatory power with respect to the natural systems taken as source of inspiration. Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science.

Cognitive Digital Twins for Smart Lifecycle Management of Built Environment and Infrastructure: Challenges, Opportunities and Practices

by Ibrahim Yitmen

This book provides knowledge into Cognitive Digital Twins for smart lifecycle management of built environment and infrastructure focusing on challenges and opportunities. It focuses on the challenges and opportunities of data-driven cognitive systems by integrating the heterogeneous data from multiple resources that can easily be used in a machine learning model and adjust the algorithms. It comprises Digital Twins incorporating cognitive features that will enable sensing complex and unpredicted behavior and reason about dynamic strategies for process optimization to support decision-making in lifecycle management of the built environment and infrastructure. The book introduces the Knowledge Graph (KG)-centric framework for Cognitive Digital Twins involving process modeling and simulation, ontology-based Knowledge Graph, analytics for process optimizations, and interfaces for data operability. It offers contributions of Cognitive Digital Twins for the integration of IoT, Big data, AI, smart sensors, machine learning and communication technologies, all connected to a novel paradigm of self-learning hybrid models with proactive cognitive capabilities. The book presents the topologies of models described for autonomous real time interpretation and decision-making support of complex system development based on Cognitive Digital Twins with applications in critical domains such as maintenance of complex engineering assets in built environment and infrastructure. It offers the essential material to enlighten pertinent research communities of the state-of-the-art research and the latest development in the area of Cognitive Digital Twins, as well as a valuable reference for planners, designers, developers, and ICT experts who are working towards the development and implementation of autonomous Cognitive IoT based on big data analytics and context–aware computing.

Cognitive Digital Twins for Smart Lifecycle Management of Built Environment and Infrastructure: Challenges, Opportunities and Practices


This book provides knowledge into Cognitive Digital Twins for smart lifecycle management of built environment and infrastructure focusing on challenges and opportunities. It focuses on the challenges and opportunities of data-driven cognitive systems by integrating the heterogeneous data from multiple resources that can easily be used in a machine learning model and adjust the algorithms. It comprises Digital Twins incorporating cognitive features that will enable sensing complex and unpredicted behavior and reason about dynamic strategies for process optimization to support decision-making in lifecycle management of the built environment and infrastructure. The book introduces the Knowledge Graph (KG)-centric framework for Cognitive Digital Twins involving process modeling and simulation, ontology-based Knowledge Graph, analytics for process optimizations, and interfaces for data operability. It offers contributions of Cognitive Digital Twins for the integration of IoT, Big data, AI, smart sensors, machine learning and communication technologies, all connected to a novel paradigm of self-learning hybrid models with proactive cognitive capabilities. The book presents the topologies of models described for autonomous real time interpretation and decision-making support of complex system development based on Cognitive Digital Twins with applications in critical domains such as maintenance of complex engineering assets in built environment and infrastructure. It offers the essential material to enlighten pertinent research communities of the state-of-the-art research and the latest development in the area of Cognitive Digital Twins, as well as a valuable reference for planners, designers, developers, and ICT experts who are working towards the development and implementation of autonomous Cognitive IoT based on big data analytics and context–aware computing.

The Cognitive Dynamics of Computer Science: Cost-Effective Large Scale Software Development (Wiley - IEEE)

by Szabolcs Michael de Gyurky

A groundbreaking, unifying theory of computer science for low-cost, high-quality software The Cognitive Dynamics of Computer Science represents the culmination of more than thirty years of the author's hands-on experience in software development, which has resulted in a remarkable and sensible philosophy and practice of software development. It provides a groundbreaking ontology of computer science, while describing the processes, methodologies, and constructs needed to build high-quality, large-scale computer software systems on schedule and on budget. Based on his own experience in developing successful, low-cost software projects, the author makes a persuasive argument for developers to understand the philosophical underpinnings of software. He asserts that software in reality is an abstraction of the human thought system. The author draws from the seminal works of the great German philosophers--Kant, Hegel, and Schopenhauer--and recasts their theories of human mind and thought to create a unifying theory of computer science, cognitive dynamics, that opens the door to the next generation of computer science and forms the basic architecture for total autonomy. * Four detailed cases studies effectively demonstrate how philosophy and practice merge to meet the objective of high-quality, low-cost software. * The Autonomous Cognitive System chapter sets forth a model for a completely autonomous computer system, using the human thought system as the model for functional architecture and the human thought process as the model for the functional data process. * Although rooted in philosophy, this book is practical, addressing all the key areas that software professionals need to master in order to remain competitive and minimize costs, such as leadership, management, communication, and organization. This thought-provoking work will change the way students and professionals in computer science and software development conceptualize and perform their work. It provides them with both a philosophy and a set of practical tools to produce high-quality, low-cost software.

The Cognitive Early Warning Predictive System Using the Smart Vaccine: The New Digital Immunity Paradigm for Smart Cities and Critical Infrastructure

by Rocky Termanini

This book introduces the Cognitive Early Warning Predictive System (CEWPS ) as the new digital immune system. Similar to the human immune system, CEWPS relies on true or "inoculated" sickness experience to defend the body. The book also introduces The Smart Vaccine an intelligent agent that manages all the vaccination-as-a-service on the cloud before an attack happens. The book illustrates the current landscape of cyber warfare, highlights the vulnerabilities of critical infrastructure, and identifies the shortcomings of AVT. Next, it describes the concept, the architecture, and the enabling technologies required to build a digital immune system.

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