The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodol- ogy is adapted and applied for transparency and justifications of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework.
Insight into IoT Applications and Common Practice Challengesijtsrd
IoT caused a revolution in the technological world. Not only is the IoT related to computers, people or cell phones but also to various sensors, actuators, vehicles, and other modern appliances. There are around 14 billion interconnected digital devices across the globe i.e. almost 2 devices per human being on earth. The IoT serves as a medium to connect non living things to the internet to transfer information from one point to another in their community network which automates processes and ultimately makes the life of human beings convenient. The subsequent result of amalgamating internet connectivity with powerful data analysis is a complete change in the way we humans work and live. The most vital characteristics of IoT include connectivity, active engagement, sensors, artificial intelligence, and small device use. All of this creates many challenges that need to be solved to keep this technology to continue expanding. In this paper, we have identified various applications of IoT based on recent technological and business trends and highlighted the existing challenges faced by IoT which need to be addressed considering the exponential acceptance of the concept globally and the way those challenges had been addressed in the past. We have also made a few comments on the way such challenges are being attempted to be resolved now. This paper presents the current status Internet of Things IoT in terms of technical details, and applications. Also, this paper opens a window for future work on the historical approach to study and address IoT challenges. Lubna Alazzawi | Jamal Alotaibi "Insight into IoT Applications and Common Practice Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30286.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30286/insight-into-iot-applications-and-common-practice-challenges/lubna-alazzawi
In this presentation, Vipul introduces IoT, talks about why he chose IoT and latest trends in that domain. Vipul loves all things related to data and he is interested in data mining for monetization.
Webinos is a collective project to make the web work for apllications aiming to design an open source platform and software components for the future Internet in the form of web runtime extensions to enable web services to be used and shared consistently and securely over a broad spectrum of converged and connective devices including mobile, pc, home-media(tv) and in car-units.
State regulation of the IoT in the Russian Federation: Fundamentals and chall...IJECEIAES
The purpose of this section is to study the problems with implementing technical and legal regulations for the development of public administration functions in the Russian Federation when using the internet of things (IoT). The introduction is based on an analysis of regulatory legal acts and presents the main strategic directions for the development of public administration functions in the Russian federation when using IoT. State reports, scientific literature, a system of technical and legal regulation are analyzed, and the main problems of implementing the IoT that impede the achievement of effective public administration are studied. The Russian practice of using IoT in various economic areas is investigated. Based on an analysis of the mechanisms for ensuring data safety of information technology users in the Russian federation, problems were investigated, such as the collecting data through IoT, including publicly available personal data in order to profile human activities, and creating of a digital twin of a person. The social constraints for introducing distributed registry technologies are users' distrust in the field of data privacy protection and mathematical algorithms that are used to establish trust in a digital environment instead of trusted centralized intermediaries; these problems were also analyzed. The Russian approach was analyzed in comparison to European experience in this field. To ensure information security and the possibility of its distribution, the IoT is revealed.
Injecting (Micro)Intelligence in the IoT: Logic-based Approaches for (M)MASAndrea Omicini
Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject (micro) intelligence ubiquitously, fears compel the behaviour of intelligent systems to be observable, explainable, and accountable.
Whereas the first wave of the new "AI Era" was mostly heralded by non-symbolic approaches, features like explainability are better provided by symbolic techniques.
In this talk we focus on logic-based approaches, and discuss their potential in pervasive scenarios like the IoT and open (M)MAS along with our latest results in the field.
Andrea Omicini, Roberta Calegari
Invited Talk
MMAS 2018, Stockholm, Sweden, 14 July 2018
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
Law, Ethics and Tech Aspects for an Irrevocable BlockChain Based Curriculum V...eraser Juan José Calderón
Law, Ethics and Tech Aspects for an Irrevocable
BlockChain Based Curriculum Vitae Created by Big
Data Analytics Fed by Internet of Things, Sensors and
Approved Data Sources. Vasilios Kanavas, Athanasios Zisopoulos & Konstantinos Spinthiropoulos
Insight into IoT Applications and Common Practice Challengesijtsrd
IoT caused a revolution in the technological world. Not only is the IoT related to computers, people or cell phones but also to various sensors, actuators, vehicles, and other modern appliances. There are around 14 billion interconnected digital devices across the globe i.e. almost 2 devices per human being on earth. The IoT serves as a medium to connect non living things to the internet to transfer information from one point to another in their community network which automates processes and ultimately makes the life of human beings convenient. The subsequent result of amalgamating internet connectivity with powerful data analysis is a complete change in the way we humans work and live. The most vital characteristics of IoT include connectivity, active engagement, sensors, artificial intelligence, and small device use. All of this creates many challenges that need to be solved to keep this technology to continue expanding. In this paper, we have identified various applications of IoT based on recent technological and business trends and highlighted the existing challenges faced by IoT which need to be addressed considering the exponential acceptance of the concept globally and the way those challenges had been addressed in the past. We have also made a few comments on the way such challenges are being attempted to be resolved now. This paper presents the current status Internet of Things IoT in terms of technical details, and applications. Also, this paper opens a window for future work on the historical approach to study and address IoT challenges. Lubna Alazzawi | Jamal Alotaibi "Insight into IoT Applications and Common Practice Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30286.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30286/insight-into-iot-applications-and-common-practice-challenges/lubna-alazzawi
In this presentation, Vipul introduces IoT, talks about why he chose IoT and latest trends in that domain. Vipul loves all things related to data and he is interested in data mining for monetization.
Webinos is a collective project to make the web work for apllications aiming to design an open source platform and software components for the future Internet in the form of web runtime extensions to enable web services to be used and shared consistently and securely over a broad spectrum of converged and connective devices including mobile, pc, home-media(tv) and in car-units.
State regulation of the IoT in the Russian Federation: Fundamentals and chall...IJECEIAES
The purpose of this section is to study the problems with implementing technical and legal regulations for the development of public administration functions in the Russian Federation when using the internet of things (IoT). The introduction is based on an analysis of regulatory legal acts and presents the main strategic directions for the development of public administration functions in the Russian federation when using IoT. State reports, scientific literature, a system of technical and legal regulation are analyzed, and the main problems of implementing the IoT that impede the achievement of effective public administration are studied. The Russian practice of using IoT in various economic areas is investigated. Based on an analysis of the mechanisms for ensuring data safety of information technology users in the Russian federation, problems were investigated, such as the collecting data through IoT, including publicly available personal data in order to profile human activities, and creating of a digital twin of a person. The social constraints for introducing distributed registry technologies are users' distrust in the field of data privacy protection and mathematical algorithms that are used to establish trust in a digital environment instead of trusted centralized intermediaries; these problems were also analyzed. The Russian approach was analyzed in comparison to European experience in this field. To ensure information security and the possibility of its distribution, the IoT is revealed.
Injecting (Micro)Intelligence in the IoT: Logic-based Approaches for (M)MASAndrea Omicini
Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject (micro) intelligence ubiquitously, fears compel the behaviour of intelligent systems to be observable, explainable, and accountable.
Whereas the first wave of the new "AI Era" was mostly heralded by non-symbolic approaches, features like explainability are better provided by symbolic techniques.
In this talk we focus on logic-based approaches, and discuss their potential in pervasive scenarios like the IoT and open (M)MAS along with our latest results in the field.
Andrea Omicini, Roberta Calegari
Invited Talk
MMAS 2018, Stockholm, Sweden, 14 July 2018
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
Law, Ethics and Tech Aspects for an Irrevocable BlockChain Based Curriculum V...eraser Juan José Calderón
Law, Ethics and Tech Aspects for an Irrevocable
BlockChain Based Curriculum Vitae Created by Big
Data Analytics Fed by Internet of Things, Sensors and
Approved Data Sources. Vasilios Kanavas, Athanasios Zisopoulos & Konstantinos Spinthiropoulos
CUbRIK tutorial at ICWE 2013: part 1 Introduction to Human ComputationCUbRIK Project
2013, July 8
Part 1 of the tutorial illustrated at ICWE 2013, by Alessandro Bozzon (Delft University of Technology)
Crowdsourcing and human computation are novel disciplines that enable the design of computation processes that include humans as actors for task execution. In such a context, Games With a Purpose are an effective mean to channel, in a constructive manner, the human brainpower required to perform tasks that computers are unable to perform, through computer games. This tutorial introduces the core research questions in human computation, with a specific focus on the techniques required to manage structured and unstructured data. The second half of the tutorial delves into the field of game design for serious task, with an emphasis on games for human computation purposes. Our goal is to provide participants with a wide, yet complete overview of the research landscape; we aim at giving practitioners a solid understanding of the best practices in designing and running human computation tasks, while providing academics with solid references and, possibly, promising ideas for their future research activities.
Towards Internet of Things: Survey and Future VisionCSCJournals
Internet of things is a promising research due to its importance in many commerce, industry, and education applications. Recently, new applications and research challenges in numerous areas of Internet of things are fired. In this paper, we discuss the history of Internet of things, different proposed architectures of Internet of things, research challenges and open problems related to the Internet of things. We also introduce the concept of Internet of things database and discuss about the future vision of Internet of things. These are the manuscript preparation guidelines used as a standard template for all journal submissions. Author must follow these instructions while preparing/modifying these guidelines.
Discovering and Understanding The Security Issues In IoT CloudCSCJournals
The rapid growth and adoption of IoT technologies in sectors of life are challenged by the resources constrained IoT devices. However, the growth of IoT technologies can be enhanced by integrating them with cloud computing. Hence, a new area of computing called IoT Cloud or CloudIoT has emerged. That is, the data collected from the IoT technologies are stored and processed in the cloud infrastructure so that IoT technologies are relived from resources constrained issue. As a result, some new classes of security and privacy issues are introduced. This paper presents security issues pertaining to IoT cloud.
Secure Modern Healthcare System Based on Internet of Things and Secret Sharin...Eswar Publications
The Internet of Things (IoT), is a concept that describes how objects that we are used in daily life will interact and negotiate with other objects over the internet. The amount of devices with Wi-Fi capabilities and built-in sensors keeps on increasing. IoT combines smart devices to provide smart services and applications like smart cities, smart healthcare, smart home, and digital farm etc. But it is very crucial to secure connected IoT devices and networks because of the nature of IoT system. In this paper, the existing works are analyzed and an IoT based
healthcare system architecture is proposed. An authentication scheme to enhance the security of the proposed healthcare system is also present.
The Internet of Things (IoT) concept has recently been presented as the next revolution and a part of the internet of the future. IoT consists of billions of uniquely identified smart objects ‘things’ with communication ability over the internet
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
Internet of Things: Surveys for Measuring Human Activities from Everywhere IJECEIAES
The internet of things (IoT), also called internet of all, is a new paradigm that combines several technologies such as computers, the internet, sensors network, radio frequency identification (RFID), communication technology and embedded systems to form a system that links the real worlds with digital worlds. With an increase in the deployment of smart objects, the internet of things should have a significant impact on human life in the near future. To understand the development of the IoT, this paper reviews the current research of the IoT, key technologies, the main applications of the IoT in various fields, and identifies research challenges. A main contribution of this review article is that it summarizes the current state of the IoT technology in several areas, and also the applications of IoT that cause side effects on our environment for monitoring and evaluation of the impact of human activity on the environment around us, and also provided an overview of some of the main challenges and application of IoT. This article presents not only the problems and challenges of IoT, but also solutions that help overcome some of the problems and challenges.
Computer Science is an ever-changing field with new inventions each day. Here are the latest trends in the field of computer science which are making their mark in this era of digitization.
Source: http://www.techsparks.co.in
Challenges and Opportunities of Internet of Things in Healthcare IJECEIAES
The Internet of Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems.
FUTURE AND CHALLENGES OF INTERNET OF THINGS ijcsit
The world is moving forward at a fast pace, and the credit goes to ever growing technology. One such
concept is IOT (Internet of things) with which automation is no longer a virtual reality. IOT connects
various non-living objects through the internet and enables them to share information with their community
network to automate processes for humans and makes their lives easier. The paper presents the future
challenges of IoT , such as the technical (connectivity , compatibility and longevity , standards , intelligent
analysis and actions , security), business ( investment , modest revenue model etc. ), societal (changing
demands , new devices, expense, customer confidence etc. ) and legal challenges ( laws, regulations,
procedures, policies etc. ). A section also discusses the various myths that might hamper the progress of
IOT, security of data being the most critical factor of all. An optimistic approach to people in adopting the
unfolding changes brought by IOT will also help in its growth.
in the wake of this urban innovation wind, the smart city, nicknamed the "Intelligent city," a model promoted since the growth of digital whose dynamics is based on the use of information and communication technologies. It is a concept based on a holistic approach to the integration of different information systems in sectors such as transportation, health, energy, the cleanliness that should translate into a net improvement in the daily life of the inhabitants. These new information and communications technologies (NICT) Such as big data, Internet of Things are the element that inspired the concept of smart city. This article discusses the architectural portion of the intelligent city based on the new technologies as well as a first step for a future study on the mobility and the behavior of citizens in the intelligent citiesby based on the Human predisposition to the game.
In the recent years, Internet of Things (IoT) has acquired a remarkable attention. IoT projects a world where billions of smart, interacting things are able to offer various services to near and remote entities. This innovative technology enables users to identify and control services. Customers can benefit from the functional guidance. Therefore, the voice of customers is transmitted to manufacturers. The benefit and welfare that the IoT brings about are undeniable; on the other hand, there are some challenges to apply IoT. The main objective of this study is to reveal the usability challenges of IoT in developing countries through a detailed literature survey.
Artificial Intelligence and the Internet of Things in Industry 4.0Petar Radanliev
This paper presents a new design for artificial intelligence in cyber-physical systems. We present a survey of principles, policies, design actions and key technologies for CPS, and discusses the state of art of the technology in a qualitative perspec- tive. First, literature published between 2010 and 2021 is reviewed, and compared with the results of a qualitative empirical study that correlates world leading Industry 4.0 frameworks. Second, the study establishes the present and future techniques for increased automation in cyber-physical systems. We present the cybersecurity requirements as they are changing with the integration of artificial intelligence and internet of things in cyber-physical systems. The grounded theory methodology is applied for analysis and modelling the connections and interdependencies between edge components and automation in cyber-physical systems. In addition, the hierarchical cascading methodology is used in combination with the taxonomic clas- sifications, to design a new integrated framework for future cyber-physical systems. The study looks at increased automation in cyber-physical systems from a technical and social level.
CUbRIK tutorial at ICWE 2013: part 1 Introduction to Human ComputationCUbRIK Project
2013, July 8
Part 1 of the tutorial illustrated at ICWE 2013, by Alessandro Bozzon (Delft University of Technology)
Crowdsourcing and human computation are novel disciplines that enable the design of computation processes that include humans as actors for task execution. In such a context, Games With a Purpose are an effective mean to channel, in a constructive manner, the human brainpower required to perform tasks that computers are unable to perform, through computer games. This tutorial introduces the core research questions in human computation, with a specific focus on the techniques required to manage structured and unstructured data. The second half of the tutorial delves into the field of game design for serious task, with an emphasis on games for human computation purposes. Our goal is to provide participants with a wide, yet complete overview of the research landscape; we aim at giving practitioners a solid understanding of the best practices in designing and running human computation tasks, while providing academics with solid references and, possibly, promising ideas for their future research activities.
Towards Internet of Things: Survey and Future VisionCSCJournals
Internet of things is a promising research due to its importance in many commerce, industry, and education applications. Recently, new applications and research challenges in numerous areas of Internet of things are fired. In this paper, we discuss the history of Internet of things, different proposed architectures of Internet of things, research challenges and open problems related to the Internet of things. We also introduce the concept of Internet of things database and discuss about the future vision of Internet of things. These are the manuscript preparation guidelines used as a standard template for all journal submissions. Author must follow these instructions while preparing/modifying these guidelines.
Discovering and Understanding The Security Issues In IoT CloudCSCJournals
The rapid growth and adoption of IoT technologies in sectors of life are challenged by the resources constrained IoT devices. However, the growth of IoT technologies can be enhanced by integrating them with cloud computing. Hence, a new area of computing called IoT Cloud or CloudIoT has emerged. That is, the data collected from the IoT technologies are stored and processed in the cloud infrastructure so that IoT technologies are relived from resources constrained issue. As a result, some new classes of security and privacy issues are introduced. This paper presents security issues pertaining to IoT cloud.
Secure Modern Healthcare System Based on Internet of Things and Secret Sharin...Eswar Publications
The Internet of Things (IoT), is a concept that describes how objects that we are used in daily life will interact and negotiate with other objects over the internet. The amount of devices with Wi-Fi capabilities and built-in sensors keeps on increasing. IoT combines smart devices to provide smart services and applications like smart cities, smart healthcare, smart home, and digital farm etc. But it is very crucial to secure connected IoT devices and networks because of the nature of IoT system. In this paper, the existing works are analyzed and an IoT based
healthcare system architecture is proposed. An authentication scheme to enhance the security of the proposed healthcare system is also present.
The Internet of Things (IoT) concept has recently been presented as the next revolution and a part of the internet of the future. IoT consists of billions of uniquely identified smart objects ‘things’ with communication ability over the internet
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
Internet of Things: Surveys for Measuring Human Activities from Everywhere IJECEIAES
The internet of things (IoT), also called internet of all, is a new paradigm that combines several technologies such as computers, the internet, sensors network, radio frequency identification (RFID), communication technology and embedded systems to form a system that links the real worlds with digital worlds. With an increase in the deployment of smart objects, the internet of things should have a significant impact on human life in the near future. To understand the development of the IoT, this paper reviews the current research of the IoT, key technologies, the main applications of the IoT in various fields, and identifies research challenges. A main contribution of this review article is that it summarizes the current state of the IoT technology in several areas, and also the applications of IoT that cause side effects on our environment for monitoring and evaluation of the impact of human activity on the environment around us, and also provided an overview of some of the main challenges and application of IoT. This article presents not only the problems and challenges of IoT, but also solutions that help overcome some of the problems and challenges.
Computer Science is an ever-changing field with new inventions each day. Here are the latest trends in the field of computer science which are making their mark in this era of digitization.
Source: http://www.techsparks.co.in
Challenges and Opportunities of Internet of Things in Healthcare IJECEIAES
The Internet of Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems.
FUTURE AND CHALLENGES OF INTERNET OF THINGS ijcsit
The world is moving forward at a fast pace, and the credit goes to ever growing technology. One such
concept is IOT (Internet of things) with which automation is no longer a virtual reality. IOT connects
various non-living objects through the internet and enables them to share information with their community
network to automate processes for humans and makes their lives easier. The paper presents the future
challenges of IoT , such as the technical (connectivity , compatibility and longevity , standards , intelligent
analysis and actions , security), business ( investment , modest revenue model etc. ), societal (changing
demands , new devices, expense, customer confidence etc. ) and legal challenges ( laws, regulations,
procedures, policies etc. ). A section also discusses the various myths that might hamper the progress of
IOT, security of data being the most critical factor of all. An optimistic approach to people in adopting the
unfolding changes brought by IOT will also help in its growth.
in the wake of this urban innovation wind, the smart city, nicknamed the "Intelligent city," a model promoted since the growth of digital whose dynamics is based on the use of information and communication technologies. It is a concept based on a holistic approach to the integration of different information systems in sectors such as transportation, health, energy, the cleanliness that should translate into a net improvement in the daily life of the inhabitants. These new information and communications technologies (NICT) Such as big data, Internet of Things are the element that inspired the concept of smart city. This article discusses the architectural portion of the intelligent city based on the new technologies as well as a first step for a future study on the mobility and the behavior of citizens in the intelligent citiesby based on the Human predisposition to the game.
In the recent years, Internet of Things (IoT) has acquired a remarkable attention. IoT projects a world where billions of smart, interacting things are able to offer various services to near and remote entities. This innovative technology enables users to identify and control services. Customers can benefit from the functional guidance. Therefore, the voice of customers is transmitted to manufacturers. The benefit and welfare that the IoT brings about are undeniable; on the other hand, there are some challenges to apply IoT. The main objective of this study is to reveal the usability challenges of IoT in developing countries through a detailed literature survey.
Artificial Intelligence and the Internet of Things in Industry 4.0Petar Radanliev
This paper presents a new design for artificial intelligence in cyber-physical systems. We present a survey of principles, policies, design actions and key technologies for CPS, and discusses the state of art of the technology in a qualitative perspec- tive. First, literature published between 2010 and 2021 is reviewed, and compared with the results of a qualitative empirical study that correlates world leading Industry 4.0 frameworks. Second, the study establishes the present and future techniques for increased automation in cyber-physical systems. We present the cybersecurity requirements as they are changing with the integration of artificial intelligence and internet of things in cyber-physical systems. The grounded theory methodology is applied for analysis and modelling the connections and interdependencies between edge components and automation in cyber-physical systems. In addition, the hierarchical cascading methodology is used in combination with the taxonomic clas- sifications, to design a new integrated framework for future cyber-physical systems. The study looks at increased automation in cyber-physical systems from a technical and social level.
A SOLUTION FRAMEWORK FOR MANAGING INTERNET OF THINGS (IOT)IJCNCJournal
Internet of Things (IoT) refers to heterogeneous systems and devices (often referred to as smart objects) that connect to the internet, and is an emerging and active area of research with tremendous technological,
social, and economical value for a hyper-connected world. In this paper, we will discuss how billions of these internet connected devices and machines will change the future in which we shall live, communicate and do the business. The devices, which would be connected to the internet, could vary from simple systems on chip (SOC) without any Operating System (OS) to highly powerful processor with intelligent OS with widely varying processing capability and diverse protocol support. Many of these devices can also communicate with each other directly in a dynamic manner. A key challenge is: how to manage such a diverse set of devices of such massive scale in a secured and effective manner without breaching privacy. In this paper, we will discuss various management issues and challenges related to different communication
protocol support and models, device management, security, privacy, scalability, availability and analytic support, etc., in managing IoT. The key contribution of this paper is proposal of a reference management system architecture based on cloud technology in addressing various issues related to anagement of IoThaving billions of smart objects.
The idea is to create a social network of sensors in which various sensors integrated to intel Galileo will send the data to the user.
Nowadays using various social networking sites like Facebook, twitter, google+ has become too main stream.
Now the idea is to integrate our home status to these social networking sites that is, creating a “Galileo link”.
Home status will be comprised of various readings taken by the sensors like IR sensor, LDR, temperature sensor.
Sensors send data to intel Galileo then Galileo acts as a client and sends that data to the social networking site.
For example in Facebook an account is created and that account is registered on Facebook developer. As soon as the account is registered on Facebook developer it creates an access token.
Access token is then included in python script running in the Galileo device.
Hence our data can be seen in our news feed and we just have to add the registered account as our friend
Application and Usefulness of Internet of Things in Information TechnologyDr. Amarjeet Singh
The Internet of Things (IoT) is a system of
interrelated computing devices, mechanical and digital
machines, objects, animals or people that are provided with
unique identifiers and the ability to transfer data over a
network without requiring human-to-human or human-tocomputer interaction. It is an ambiguous term, but it is fast
becoming a tangible technology that can be applied in data
centers to collect information on just about anything that
IT wants to control. IoT has evolved from the convergence
of wireless technologies, micro-electromechanical systems
(MEMS), microservices and the internet. The convergence
has helped tear down the silo walls between operational
technology (OT) and information technology (IT), allowing
unstructured machine-generated data to be analyzed for
insights that will drive improvements. The Internet of
Things (IoT) is essentially a system of machines or objects
outfitted with data-collecting technologies so that those
objects can communicate with one another. The machineto-machine (M2M) data that is generated has a wide range
of uses, but is commonly seen as a way to determine the
health and status of things -- inanimate or living.
Cyber risk at the edge: current and future trends on cyber risk analytics and...Petar Radanliev
Digital technologies have changed the way supply chain operations are structured. In this article, we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks. A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0, with a specific focus on the mitigation of cyber risks. An analytical framework is presented, based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies. This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks.
The Internet of Things (IoT), also referred to as the Internet of Objects, will change everything—including ourselves. This may seem like a bold statement, but consider the impact the Internet already had on education, science, communication, business, government, and humanity. Clearly, the Internet is one of the most important and a powerful creation in all of human history. This paper discussesIOT architecture, IOT applications and limitations of IOT.
Data management and enterprise architectures for responsible AI services .pptxMolnrBlint4
Big data is becoming a reality. Complex and difficult-to-understand
data may be found in a wide range of industries. Big data is a critical component
of enterprise services and technology architectures. Data science techniques
and methodologies can be applied in many different aspects of the working
of companies. In this paper, first, as a background, we provide an overview
of knowledge management practices and data analysis strategies and techniques
in the daily operations of companies working towards development of AI
agents, and the need in particular companies can develop human centric AI solutions;
Then, we discuss the basics for cross-disciplinary research, in which we
stress the need to re-think development processes of AI services and make them
more responsible, and we define research questions to investigate the problem.
As the research proposal discusses, companies and public institutions, can create
and develop new responsible, ethical, and transparent AI services.
Artificial Intelligence and Quantum CryptographyPetar Radanliev
Dr Petar Radanliev
Department of Computer Sciences
University of Oxford
Abstract:
The technological advancements made in recent times, particularly in Artificial Intelligence (AI) and Quantum Computing, have brought about significant changes in technology. These advancements have profoundly impacted quantum cryptography, a field where AI methodologies hold tremendous potential to enhance the efficiency and robustness of cryptographic systems. However, the emergence of quantum computers has created a new challenge for existing security algorithms, commonly called the 'quantum threat'. Despite these challenges, there are promising avenues for integrating neural network-based AI in cryptography, which has significant implications for future digital security paradigms. This summary highlights the key themes in the intersection of AI and quantum cryptography, including the potential benefits of AI-driven cryptography, the challenges that need to be addressed, and the prospects of this interdisciplinary research area.
Keywords: Artificial Intelligence, Quantum Algorithms, Neural Networks, Quantum-AI Integration, Quantum Threats, AI-enhanced Security, Quantum Information Processing.
Artificial Intelligence and Quantum CryptographyPetar Radanliev
Abstract:
The technological advancements made in recent times, particularly in Artificial Intelligence (AI) and Quantum Computing, have brought about significant changes in technology. These advancements have profoundly impacted quantum cryptography, a field where AI methodologies hold tremendous potential to enhance the efficiency and robustness of cryptographic systems. However, the emergence of quantum computers has created a new challenge for existing security algorithms, commonly called the 'quantum threat'. Despite these challenges, there are promising avenues for integrating neural network-based AI in cryptography, which has significant implications for future digital security paradigms. This summary highlights the key themes in the intersection of AI and quantum cryptography, including the potential benefits of AI-driven cryptography, the challenges that need to be addressed, and the prospects of this interdisciplinary research area.
Keywords: Artificial Intelligence, Quantum Algorithms, Neural Networks, Quantum-AI Integration, Quantum Threats, AI-enhanced Security, Quantum Information Processing.
Cyber Diplomacy: Defining the Opportunities for Cybersecurity and Risks from Artificial Intelligence, IoT, Blockchains, and Quantum Computing
Abstract: Cyber diplomacy is critical in dealing with the digital era's evolving cybersecurity dangers and possibilities. This article investigates the impact of Artificial Intelligence (AI), the Internet of Things (IoT), Blockchains, and Quantum Computing on cyber diplomacy. AI holds the potential for proactive threat identification and response, while IoT enables international information sharing. Blockchains enable secure data sharing and document verification, but they also pose new threats, such as AI-driven cyber-attacks, IoT privacy breaches, blockchain vulnerabilities, and the potential for quantum computing to break encryption. This article conducts case study reviews in combination with secondary data analysis and emphasises the value of international cooperation in developing global norms and frameworks to control responsible technology adoption. Cyber diplomacy can promote cybersecurity, protect national interests, and foster mutual trust among nations in the digital sphere by capitalising on possibilities and reducing threats.
PhD Thesis:
Blockchain Cybersecurity
Dr Petar Radanliev
University of Oxford
PhD Thesis:
"Blockchain Cybersecurity: A Comprehensive Study"
Dr Petar Radanliev
University of Oxford
Abstract:
This thesis presents an exhaustive exploration of the interplay between blockchain technology and cybersecurity. It delves into how blockchain can revolutionise cybersecurity practices, addressing existing challenges and opening up new avenues for secure digital interactions. The study provides a thorough analysis of blockchain's inherent security features, such as decentralisation, immutability, and transparency, and how these attributes contribute to enhancing cybersecurity across various domains. Additionally, the thesis examines potential vulnerabilities within blockchain systems and proposes strategies for mitigating these risks. By combining theoretical insights with practical case studies, this work aims to offer a holistic view of blockchain's role in shaping the future landscape of cybersecurity.
Chapter 1: Introduction
Overview of Blockchain Technology
Cybersecurity Challenges in the Digital Age
Objectives and Scope of the Study
Chapter 2: Fundamentals of Blockchain Technology
History and Evolution of Blockchain
Key Components and Functioning of Blockchain Systems
Types of Blockchain: Public, Private, and Consortium
Chapter 3: Blockchain in Cybersecurity
Decentralisation as a Security Feature
Immutability and Data Integrity
Transparency and Trust in Blockchain Systems
Chapter 4: Blockchain Applications in Cybersecurity
Use Cases in Various Industries
Blockchain in Identity Management and Authentication
Secure Transactions and Smart Contracts
Chapter 5: Vulnerabilities and Risks in Blockchain
Analysis of Known Blockchain Vulnerabilities
Potential Attack Vectors and Their Implications
Risk Mitigation Strategies and Best Practices
Chapter 6: Future Trends and Challenges
Emerging Trends in Blockchain and Cybersecurity
Scalability, Interoperability, and Regulatory Challenges
Future Research Directions
Chapter 7: Conclusion
Summary of Key Findings
Contributions to the Field of Blockchain Cybersecurity
Recommendations for Future Research and Practice
Appendices
Technical Details of Blockchain Protocols
Case Studies and Practical Examples
Bibliography
Comprehensive List of Academic References and Key Sources
This thesis contributes to the existing body of knowledge by providing a detailed analysis of blockchain's potential and limitations in the realm of cybersecurity, offering valuable insights for academics, industry practitioners, and policy makers.
I started my career testing security in the military and defence industries. Then, I moved into managing cyber risks in the finance world. After ten years in these fields, I returned to academics, earning my PhD, Master's, and Bachelor's degrees.
My postdoctoral work took me to several universities: Imperial College London, the University of Cambridge, MIT, and back to the University of Oxford
PhD Thesis:
Blockchain Cybersecurity
Dr Petar Radanliev
University of Oxford
PhD Thesis:
"Blockchain Cybersecurity: A Comprehensive Study"
Dr Petar Radanliev
University of Oxford
Abstract:
This thesis presents an exhaustive exploration of the interplay between blockchain technology and cybersecurity. It delves into how blockchain can revolutionise cybersecurity practices, addressing existing challenges and opening up new avenues for secure digital interactions. The study provides a thorough analysis of blockchain's inherent security features, such as decentralisation, immutability, and transparency, and how these attributes contribute to enhancing cybersecurity across various domains. Additionally, the thesis examines potential vulnerabilities within blockchain systems and proposes strategies for mitigating these risks. By combining theoretical insights with practical case studies, this work aims to offer a holistic view of blockchain's role in shaping the future landscape of cybersecurity.
Chapter 1: Introduction
Overview of Blockchain Technology
Cybersecurity Challenges in the Digital Age
Objectives and Scope of the Study
Chapter 2: Fundamentals of Blockchain Technology
History and Evolution of Blockchain
Key Components and Functioning of Blockchain Systems
Types of Blockchain: Public, Private, and Consortium
Chapter 3: Blockchain in Cybersecurity
Decentralisation as a Security Feature
Immutability and Data Integrity
Transparency and Trust in Blockchain Systems
Chapter 4: Blockchain Applications in Cybersecurity
Use Cases in Various Industries
Blockchain in Identity Management and Authentication
Secure Transactions and Smart Contracts
Chapter 5: Vulnerabilities and Risks in Blockchain
Analysis of Known Blockchain Vulnerabilities
Potential Attack Vectors and Their Implications
Risk Mitigation Strategies and Best Practices
Chapter 6: Future Trends and Challenges
Emerging Trends in Blockchain and Cybersecurity
Scalability, Interoperability, and Regulatory Challenges
Future Research Directions
Chapter 7: Conclusion
Summary of Key Findings
Contributions to the Field of Blockchain Cybersecurity
Recommendations for Future Research and Practice
Appendices
Technical Details of Blockchain Protocols
Case Studies and Practical Examples
Bibliography
Comprehensive List of Academic References and Key Sources
This thesis contributes to the existing body of knowledge by providing a detailed analysis of blockchain's potential and limitations in the realm of cybersecurity, offering valuable insights for academics, industry practitioners, and policy makers.
I started my career testing security in the military and defence industries. Then, I moved into managing cyber risks in the finance world. After ten years in these fields, I returned to academics, earning my PhD, Master's, and Bachelor's degrees.
My postdoctoral work took me to several universities: Imperial College London, the University of Cambridge, MIT, and back to the University of Oxford
The Rise and Fall of Cryptocurrencies: Defining the Economic and Social Values of Blockchain Technologies, assessing the Opportunities, and defining the Financial and Cybersecurity Risks of the Metaverse.
Ethics and Responsible AI Deployment
Abstract: As Artificial Intelligence (AI) becomes more prevalent, protecting personal privacy is a critical ethical issue that must be addressed. This article explores the need for ethical AI systems that safeguard individual privacy while complying with ethical standards. By taking a multidisciplinary approach, the research examines innovative algorithmic techniques such as differential privacy, homomorphic encryption, federated learning, international regulatory frameworks, and ethical guidelines. The study concludes that these algorithms effectively enhance privacy protection while balancing the utility of AI with the need to protect personal data. The article emphasises the importance of a comprehensive approach that combines technological innovation with ethical and regulatory strategies to harness the power of AI in a way that respects and protects individual privacy.
Artificial intelligence (AI) has the potential to significantly impact employment, social equity, and economic systems in ways that require careful ethical analysis and aggressive legislative measures to mitigate negative consequences. This means that the implications of AI in different industries, such as healthcare, finance, and transportation, must be carefully considered.
Due to the global nature of AI technology, global collaboration must be fostered to establish standards and regulatory frameworks that transcend national boundaries. This includes the establishment of ethical guidelines that AI researchers and developers worldwide should follow.
To address emergent ethical concerns with AI, future research must focus on several recommendations. Firstly, ethical considerations must be integrated into the design phase of AI systems and not treated as an afterthought. This is known as "Ethics by Design" and involves incorporating ethical standards during the development phase of AI systems to ensure that the technology aligns with ethical principles.
Secondly, interdisciplinary research that combines AI, ethics, law, social science, and other relevant domains should be promoted to produce well-rounded solutions to ethical dilemmas. This requires the participation of experts from different fields to identify and address ethical issues.
Thirdly, regulatory frameworks must be dynamic and adaptive to keep pace with the rapid evolution of AI technologies. This means that regulatory frameworks must be flexible enough to accommodate changes in AI technology while ensuring ethical standards are maintained.
Fourthly, empirical research should be conducted to understand the real-world implications of AI systems on individuals and society, which can then inform ethical principles and policies. This means that empirical data must be collected to understand how AI affects people in different contexts.
Finally, risk assessment procedures should be improved to better analyse the ethical hazards associated with AI applications.
Artificial Intelligence: Survey of Cybersecurity Capabilities, Ethical Concer...Petar Radanliev
The comprehensive survey articulates the multifaceted dimensions of Artificial Intelligence (AI), spanning its historical roots, advancements, and ethical dilemmas. It starts by tracing the intellectual lineage of AI to ancient mythology and proceeds to discuss the revolutionary contributions of Generative Pre-trained Transformers (GPT), particularly GPT-4, in problem-solving and real-world applications. The paper also delves into the darker applications of AI, including its role in cyberattacks and automated phishing. Various techniques of adversarial attacks that undermine AI systems, such as Fast Gradient Sign Method (FGSM), Jacobian-based Saliency Map Attack (JSMA), and Universal Adversarial Perturbations (UAP), are meticulously examined. The paper further expounds on Membership Inference Attacks (MIA), a significant privacy concern, and presents various strategies to defend against adversarial attacks. A global perspective on AI regulations, encompassing UK, New Zealand, the EU, and China policies, is also provided. It culminates in weighing the ethical considerations against the security risks in AI, contextualised by global crime statistics. This survey serves as an exhaustive resource for understanding AI's complexity, capabilities, and ethical implications, offering invaluable insights for researchers, policymakers, and industry experts.
Artificial Intelligence and Quantum Cryptography: A comprehensive analysis of...Petar Radanliev
The technological advancements made in recent times, particularly in Artificial Intelligence (AI) and quantum computing, have brought about significant changes in technology. These advancements have profoundly impacted quantum cryptography, a field where AI methodologies hold tremendous potential to enhance the efficiency and robustness of cryptographic systems. However, the emergence of quantum computers has created a new challenge for existing security algorithms, commonly called the 'quantum threat'. Despite these challenges, there are promising avenues for integrating neural network-based AI in cryptography, which has significant implications for future digital security paradigms. This summary highlights the key themes in the intersection of AI and quantum cryptography, including the potential benefits of AI-driven cryptography, the challenges that need to be addressed, and the future prospects of this interdisciplinary research area.
Red Teaming Generative AI and Quantum CryptographyPetar Radanliev
In the contemporary digital age, Quantum Computing and Artificial Intelligence (AI) convergence is reshaping the cyber landscape, introducing both unprecedented opportunities and potential vulnerabilities.
This research, conducted over five years, delves into the cybersecurity implications of this convergence, with a particular focus on AI/Natural Language Processing (NLP) models and quantum cryptographic protocols, notably the BB84 method and specific NIST-approved algorithms. Utilising Python and C++ as primary computational tools, the study employs a "red teaming" approach, simulating potential cyber-attacks to assess the robustness of quantum security measures. Preliminary research over 12 months laid the groundwork, which this study seeks to expand upon, aiming to translate theoretical insights into actionable, real-world cybersecurity solutions. Located at the University of Oxford's technology precinct, the research benefits from state-of-the-art infrastructure and a rich collaborative environment. The study's overarching goal is to ensure that as the digital world transitions to quantum-enhanced operations, it remains resilient against AI-driven cyber threats. The research aims to foster a safer, quantum-ready digital future through iterative testing, feedback integration, and continuous improvement. The findings are intended for broad dissemination, ensuring that the knowledge benefits academia and the global community, emphasising the responsible and secure harnessing of quantum technology.
1. Introduction: Quantum Technology, AI, and the Evolving Cybersecurity Landscape
In the contemporary technological epoch, the rapid evolution of Quantum Computing and Artificial Intelligence (AI) is reshaping our digital realm, expanding the cyber risk horizon. As we stand on the cusp of a quantum revolution, the cyber-attack surface undergoes a transformation, heralding a future rife with potential cyber threats.
2. Theoretical Underpinning
This research endeavours to construct a robust cybersecurity framework, ensuring AI's harmonious and secure integration with the Quantum Internet. Central to our exploration is evaluating AI/Natural Language Processing (NLP) models and their interaction with quintessential quantum security protocols, notably the BB84 method and select NIST-endorsed algorithms. Leveraging the computational prowess of Python and C++, we aim to critically assess the resilience of these quantum security paradigms by simulating AI-driven cyber-attacks.
3. Research Objectives
Envision a quantum-enhanced internet, operating at unparalleled speeds, yet fortified against AI-mediated cyber threats. This vision encapsulates our primary objective: to ensure that the digital advancements of the future, powered by AI, remain benevolent and secure. Over a five-year trajectory, our mission is to harness AI's potential in a manner that is beneficial and safeguarded against malevolent exploits.
Red Teaming AI and Quantum
In the contemporary digital age, Quantum Computing and Artificial Intelligence (AI) convergence is reshaping the cyber landscape, introducing both unprecedented opportunities and potential vulnerabilities.
This research, conducted over five years, delves into the cybersecurity implications of this convergence, with a particular focus on AI/Natural Language Processing (NLP) models and quantum cryptographic protocols, notably the BB84 method and specific NIST-approved algorithms. Utilising Python and C++ as primary computational tools, the study employs a "red teaming" approach, simulating potential cyber-attacks to assess the robustness of quantum security measures. Preliminary research over 12 months laid the groundwork, which this study seeks to expand upon, aiming to translate theoretical insights into actionable, real-world cybersecurity solutions. Located at the University of Oxford's technology precinct, the research benefits from state-of-the-art infrastructure and a rich collaborative environment. The study's overarching goal is to ensure that as the digital world transitions to quantum-enhanced operations, it remains resilient against AI-driven cyber threats. The research aims to foster a safer, quantum-ready digital future through iterative testing, feedback integration, and continuous improvement. The findings are intended for broad dissemination, ensuring that the knowledge benefits academia and the global community, emphasising the responsible and secure harnessing of quantum technology.
-- Introduction: Quantum Technology, AI, and the Evolving Cybersecurity Landscape
In the contemporary technological epoch, the rapid evolution of Quantum Computing and Artificial Intelligence (AI) is reshaping our digital realm, expanding the cyber risk horizon. As we stand on the cusp of a quantum revolution, the cyber-attack surface transforms, heralding a future rife with potential cyber threats.
-- Theoretical Underpinning
This research endeavours to construct a robust cybersecurity framework, ensuring AI's harmonious and secure integration with the Quantum Internet. Central to our exploration is evaluating AI/Natural Language Processing (NLP) models and their interaction with quintessential quantum security protocols, notably the BB84 method and select NIST-endorsed algorithms. Leveraging the computational prowess of Python and C++, we aim to critically assess the resilience of these quantum security paradigms by simulating AI-driven cyber-attacks.
-- Research Objectives
Envision a quantum-enhanced internet, operating at unparalleled speeds yet fortified against AI-mediated cyber threats. This vision encapsulates our primary objective: to ensure that the digital advancements of the future, powered by AI, remain benevolent and secure. Over a five-year trajectory, our mission is to harness AI's potential in a manner that is beneficial and safeguarded against malevolent exploits.
Red Teaming Generative AI/NLP, the BB84 quantum cryptography protocol and the...Petar Radanliev
In the contemporary digital age, Quantum Computing and Artificial Intelligence (AI) convergence is reshaping the cyber landscape, introducing both unprecedented opportunities and potential vulnerabilities.
This research, conducted over five years, delves into the cybersecurity implications of this convergence, with a particular focus on AI/Natural Language Processing (NLP) models and quantum cryptographic protocols, notably the BB84 method and specific NIST-approved algorithms. Utilising Python and C++ as primary computational tools, the study employs a "red teaming" approach, simulating potential cyber-attacks to assess the robustness of quantum security measures. Preliminary research over 12 months laid the groundwork, which this study seeks to expand upon, aiming to translate theoretical insights into actionable, real-world cybersecurity solutions. Located at the University of Oxford's technology precinct, the research benefits from state-of-the-art infrastructure and a rich collaborative environment. The study's overarching goal is to ensure that as the digital world transitions to quantum-enhanced operations, it remains resilient against AI-driven cyber threats. The research aims to foster a safer, quantum-ready digital future through iterative testing, feedback integration, and continuous improvement. The findings are intended for broad dissemination, ensuring that the knowledge benefits academia and the global community, emphasising the responsible and secure harnessing of quantum technology.
Cyber Diplomacy: Defining the Opportunities for Cybersecurity and Risks from Artificial Intelligence, IoT, Blockchains, and Quantum Computing
-- One of the main benefits of cyber intelligence sharing is the access to shared threat intelligence
Sharing threat intelligence on time allows for a faster and more effective reaction to cyber incidents, limiting the potential impact and minimising damage
Cyber threat intelligence sharing encourages a collaborative approach to cybersecurity, boosting collective defence efforts among organisations and nations
Sharing threat intelligence allows organisations to learn from each other's experiences, resulting in skill growth and enhanced knowledge in cybersecurity
Sharing cyber threat intelligence supports public-private cooperation, combining the skills and resources of both sectors to effectively tackle cyber threats
-- Cyber threat intelligence frequently originates in a variety of formats and patterns, making it challenging to consolidate and analyse data across several organisations efficiently.
-- CISCP is a United States government effort that promotes information sharing between federal agencies and private-sector organisations in order to improve cybersecurity
One ongoing academic effort is the Global Cyber Security Capacity Centre at the University of Oxford
GCSCC is a cybersecurity capacity-building centre, advocating an increase in the global scale, pace, quality, and impact of cybersecurity capacity-building activities.
-- Overcoming geopolitical tensions in cyber discussions is a difficult and delicate endeavour, but it is critical for developing international collaboration and effectively combating cyber threats
-- Diplomatic efforts should be directed towards identifying common ground and areas of mutual interest in cybersecurity
-- Creating avenues for regular communication and discussion can help nations create trust and understanding
-- Cyber diplomacy needs to be focused on encouraging joint research initiatives, cyber threat information exchange, and collaborative efforts to strengthen cybersecurity capabilities to build bridges and foster collaboration
Nations can collaborate to develop rules that improve cybersecurity while discouraging malevolent behaviour.
-- Several future developments are anticipated to affect the landscape of cyber diplomacy as the field of cybersecurity evolves
These developments will have a substantial impact on international cooperation, policy, and responses to growing cyber threats
One of the anticipated future trends is the emergence of international cyber norms
The creation of internationally recognised cyber norms will gain traction
Nations will work more closely together to develop common principles and standards guiding responsible state behaviour in cyberspace
Nations will need to address concerns such as AI ethics, the possible threats of autonomous cyber systems, and the development of rules for the appropriate use of AI in cyber operations.
Dance Movement Therapy in the Metaverse: A Fusion of Virtual Rhythms and Real Healing
In the vast expanse of the digital universe, where pixels and avatars reign supreme, there lies an unexpected sanctuary of healing: dance. The metaverse, a realm of virtual reality (VR), augmented reality (AR), and mixed reality (MR), is not just a playground for gamers and tech enthusiasts. It's emerging as a therapeutic space where the age-old art of dance is being reimagined. As our physical and digital worlds intertwine, dance in the metaverse is not only a testament to the evolution of art but also a beacon of hope for those grappling with mental health challenges. This immersive dance movement therapy, blending the boundaries of the real and virtual, offers not just an exhilarating physical exercise but also a transformative journey for the mind. Dive with us into this rhythmic odyssey, where every move is a step towards wellness.
Dance Movement Therapy in the Metaverse: A New Frontier for Mental HealthPetar Radanliev
-- Problem Background: Mental health issues, especially anxiety and depression, are rising globally. We need non-pharmacological interventions. This brings into light the potential of integrating alternative therapies in extended reality environments, such as the Metaverse.
-- Data Collection: Utilised wearable sensors to gather data on participants’ movements, physiological responses, and emotional feedback.
Methodology | AI and ML models: DeepDance model uses a combination of CNNs and RNNs to learn the temporal and spatial patterns of dance movements. The DeepDance model has been shown to be effective in classifying different types of dance movements, as well as in predicting the outcome of a dance performance.
-- Experimental approach: AI and ML models: Time Series Analysis
-- Key Findings: Dance Movement Therapy in extended reality environments shows potential as a beneficial alternative therapy.
Software Bill of Materials and the Vulnerability Exploitability eXchange Petar Radanliev
The UK and the U.S. are in a special relationship that requires compliance with cybersecurity regulations and cyber solid diplomacy. The Executive Order 14028 which imposes a compulsory requirement for Software Bill of Materials (SBOM), has exposed the need for deeper collaboration between the UK and the U.S. cybersecurity agencies.
We need a comprehensive cyber policy that prioritises cybersecurity as a top national priority for the UK. The UK and the U.S. have individually developed their forward-looking cybersecurity strategy to protect their critical infrastructure, businesses, and citizens from evolving cyber risks. The UK has fallen behind in following the U.S. requirements for Software Bill of Materials (SBOM) and cyber vulnerabilities. This exposes a gap in the UK and the U.S. cyber diplomacy and requires a new strategy that builds on existing collaborative efforts and shared expertise in countering cyber threats.
To bring the UK back on track with compliance with standards, legislations, and regulations in the U.S. and to strengthen the UK and the U.S. collective defence capabilities, the new strategy must prioritise improving information sharing, intelligence collaboration and collaborative cybersecurity exercises. This is particularly relevant and important in light of the difficulties SBOMs present in assuring software supply chain security.
This necessitates active participation in multilateral forums that advance cyber policy and advance global norms for cyberspace while also encouraging responsible state behaviour and addressing vulnerabilities in a coordinated fashion. The UK and the U.S. need to set the standard for promoting cyber resilience by creating a secure digital future not only for the UK and the U.S. but through coordinated efforts. The new strategy must also provide opportunities for engagement with the larger international community. The first step in doing this is to address the complexities of managing SBOMs and cyber vulnerabilities with the guiding principles of transparency, cooperation, and international stability in cyberspace.
When the level of cooperation and collaboration has been re-established, the problem of managing the vast volume of new vulnerabilities will be imposed on UK cybersecurity professionals. This study is designed to identify the solutions that would reduce the burden on U.S. cybersecurity professionals today, and the workloads on UK cybersecurity professionals in the future.
The solutions investigated in this study are based on using Generative Pre-Trained Transformers, Natural Language Processing, Artificial Intelligence, and other Machine Learning algorithms in Software Vulnerability Management. The objective of the study is to identify how such tools can be used for automations in the Software Bill of Materials (SBOM) and the Vulnerability-Exploitability eXchange (VEX).
The Rise and Fall of Cryptocurrencies: Defining the Economic and Social Value...Petar Radanliev
This paper contextualises the common queries of "why is crypto crashing?" and "why is crypto down?", the research transcends beyond the frequent market fluctuations to unravel how cryptocurrencies fundamentally work and the step-by-step process on how to create a cryptocurrency.
The Rise and Fall of Cryptocurrencies: Defining the Economic and Social Value...Petar Radanliev
The study examines blockchain technologies and their pivotal role in the evolving Metaverse, shedding light on topics such as how to invest in cryptocurrency, the mechanics behind crypto mining, and strategies to effectively buy and trade cryptocurrencies. Through an interdisciplinary approach, the research transitions from the fundamental principles of fintech investment strategies to the overarching implications of blockchain within the Metaverse. Alongside exploring machine learning potentials in financial sectors and risk assessment methodologies, the study critically assesses whether developed or developing nations are poised to reap greater benefits from these technologies. Moreover, it probes into both enduring and dubious crypto projects, drawing a distinct line between genuine blockchain applications and Ponzi-like schemes. The conclusion resolutely affirms the continuing dominance of blockchain technologies, underlined by a profound exploration of their intrinsic value and a reflective commentary by the author on the potential risks confCybersecurity Risks ronting individual investors.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
2. AI & SOCIETY
1 3
human-like performance, triggering the creation of collec-
tive from desires of many subjects.
One such intrusive technology is the Industrial Inter-
net of Things (IIoT). Internet of Things (IoT) technology
has become of considerable academic, government, and
industry interest in recent years. The IIoT can be explained
as the use of internet of things technologies to improve
manufacturing and industrial processes. The IIoT term
is closely related to the term Industry 4.0 (I4.0), which
represents at the same time: a paradigm shift in indus-
trial production, a generic designation for sets of strategic
initiatives to boost national industries, a technical term
to relate to new emerging business assets, processes and
services, and a brand to mark a very particular historical
and social period.
Through reviewing a considerable academic, government
and industry literature, specific research questions emerge
from the research gaps that the review has identified. There
is a significant gap in current research on how the integration
of complex and interconnected internet of things (IoT), cou-
pled in cyber physical systems (CPS), triggers inevitable and
autonomous evolution of artificial cognition. The literature
review and taxonomic analysis consider the significance of
these research gaps in the discussion on how technological
advancement results with the inevitable and autonomous
evolution of artificial cognition in complex, coupled and
interconnected socio-technical systems.
One example for Artificial Intelligence (AI) working
in combination with internet of things (IoT) devices is the
Tesla car. The car uses Artificial Intelligence (AI) to deter-
mine road conditions, optimal speed, weather, and to predict
pedestrians’ and cars’ movement. Another example, in the
context of Covid-19, is the use of smart buildings. While the
internet of things (IoT) can be used as sensors for switching
on lights and opening doors, in combination with Artificial
Intelligence (AI), it could also be used for predicting opti-
mal time for heating or cooling the building. In the future,
Artificial Intelligence (AI) in cyber physical systems (CPS)
would include health and biomedical monitoring, robotics
systems, intelligent edge devices, among many other func-
tions, and be used to correct natural disasters, human errors,
or malicious actions, etc.
Hence, this is exercise is important, because with the
increased number of internet of things (IoT) connected
devices, the role of cyber physical systems (CPS) has
changed and evolved. With the added element of Industrial
Internet of Things (IIoT) increasing productivity, efficiency
and economic benefits, and the changing role of Artificial
Intelligence (AI) used for the creation of this new economic
benefits, the current five levels of cyber physical system
architecture seems obsolete. With considerations of these
new technologies, we focus on determining a new CPS
architecture.
In this article, we refer to Artificial Intelligence (AI)
not only as a technology for reasoning, planning, learning,
and processing, but we also refer to the ability to move and
manipulate objects. This relates or research on Artificial
Intelligence (AI) with Cyber Physical Systems (CPS). By
Cyber Physical Systems (CPS), we refer to computer–human
networks, controlling physical processes, where physical
processes affect computations and vice versa. One modern
version of Cyber Physical Systems is the Internet of Things
(IoT). The Internet of Things (IoT) is one step forward in the
advancement of AI in machines and represents a system of
interrelated computing devices, capable of operating with-
out human-to-human or human-to-computer interaction. The
Industrial Internet of Things (IIoT) in this study refers to
sensors and other devices networked with industrial appli-
cations, enabling data collection, exchange, and analysis,
with the objective for increase in productivity, efficiency
and economic benefits.
The review of such systems in this paper includes the
advancements in Cyber Physical Systems (CPS), the Inter-
net of Things (IoT) in relation to Artificial Intelligence (AI)
autonomous evolution in Industry 4.0 (I4.0). In this context,
we propose the term CPS-IoT to refer to the integration of
cyber physical attributes into Industrial Internet of Things
(IIoT) systems. This integration includes advances in real-
time processing, sensing, and actuation between IIoT sys-
tems and physical domains and provides capabilities for sys-
tem analysis of the cyber and physical structures involved.
We, therefore, focus here on artificial cognition, defined as
the artificial intelligence in networked connection of people,
processes, data, and things. Therefore, artificial intelligence
in this article represents a more inclusive and encompass-
ing concept that consolidates the cyber physical attributes
of IIoT with the social aspects of the environment in which
this technology is deployed and reflects the future cognitive
makeup of IIoT/I4.0. The term artificial cognition in the con-
text of this article is used to discuss effect from the evolving
IoT services and social networks of I4.0.
This article is structured as follows: Our methodology
is described in Sect. 2. In Sect. 3, we discuss the findings
drawn from the literature review including contributions
and gaps that form artificial cognition in CPS. Section 4
produces a taxonomy for management techniques and their
significance to the discussion on artificial cognition in I4.0.
A Discussion section and a Conclusion section synthesise
our findings and ends the article.
2 Methods
The methods applied in this study consist of systematic
literature review, taxonomies derived and follows existing
research studies on this topic that apply literature review
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with taxonomy (Milano et al. 2020), in pursuit of narratives
(O’Hara 2020). Academic literature and practical studies
are consulted intensively to discuss the IoT technologies and
their relation to the I4.0. While the mainstream academic
literature offers limited insights regarding existing and
emerging cognitive developments, we use summary maps
to showcase recent developments in this field.
Our rationale is that—as the landscape of artificial cog-
nition develops and changes very quickly—merely relying
on journal publications provides too narrow a view of the
present situation. We used the analytical target cascading,
combined with the grounded theory approach (Glaser and
Strauss 1967), to construct a conceptual cascading model for
the future integration of cognition in the I4.0. These models
then inform a qualitative empirical study for the new cog-
nitive feedback mechanism approach. The chosen method
for conducting systematic literature review represented
the following: (1) searching established journal databases
and updating the findings with cross checking with google
scholar search engine; (2) creating a table of search terms
and article inclusion criteria such as relevance, peer review,
data of publication (less than 10 years), and design of stud-
ies. (3) we also considered ethical issues in relations to how
data was obtained, reported, and protected. For example,
we did not include any non-peer-reviewed studies that were
critical of different nations or organisations. We also did not
include any literature where data sources were not included.
For example, studies that claim individual company and/or
nation CPS or IoT performance was better (e.g. Huawei vs
Ericson vs Nokia) were not included if the data were not
included in the study, or if we were unable to verify the
results.
3 Literature review on cyber risk analytics
and artificial intelligence
The literature review is focused on identifying the most
prominent concepts present in current models, infrastruc-
tures and frameworks, from over 90 academic, government
and industry papers, reports, and technical notes, published
predominately between 2010 and 2020. In our search for
data records, we used predominately Google Scholar and the
Web of Science Core Collection. For selecting the academic
literature, we found Google Scholar more flexible when add-
ing more search terms. For example, when adding multi-
ple terms in the Web of Science Core Collection, with the
Boolean: AND, the search results are limited. We searched
for TOPIC: (artificial intelligence) AND TOPIC: (industrial
internet of things) AND TOPIC: (internet of things) AND
TOPIC: (cyber physical systems) AND TOPIC: (industry
4.0). This search on the Web of Science Core Collection
produced only 25 data records. If only one of the Booleans:
AND is changed to OR, then the data records change to hun-
dreds of thousands, but its relevance to the correlated topics
diminishes, and focus is placed on the one topic searched
with the Boolean: OR. We repeated the same search with
Google Scholar, with all topics TOPIC: (artificial intelli-
gence) AND TOPIC: (industrial internet of things) AND
TOPIC: (internet of things) AND TOPIC: (cyber physical
systems) AND TOPIC: (industry 4.0). The same search on
Google Scholar produced 20,700 data records. Hence, to
ensure the relevance to all of the topics we investigated, of
our selected data records, we used both the Web of Science
Core Collection and Google Scholar, but since the number of
articles was much greater on Google Scholar, we used pre-
dominately the Google Scholar search engine for analysing
the greater volume of data records. Since both databases
contain articles from the same journals, and Google Scholar
search engine is more effective in search queries on many
topics, using Booleans, we considered this as valid argument
for selecting the most relevant data records.
Since the existing CPS architecture that we reviewed and
tried to update was published in 2015, we tried to include
literature predominately from the time period between 2015
and 2020. However, some of the most important literature
from 2010 to 2020 is also included, and for inclusiveness,
a very few articles from before 2010 are included in the
review. Considering the purpose of this review was to update
our understanding of CPS architecture, we did not conduct
a historic analysis of all relevant literature. Instead, we
considered that the CPS architecture from 2015 included
knowledge from historic literature, and our aim was to
update that knowledge with the most recent findings on CPS
architecture.
Concepts that are recognised as most prominent are cat-
egorised following the grounded theory approach for catego-
rising emerging concepts (Glaser and Strauss 1967). This
process is detailed in the ‘Methods’ chapter. As a result of
following the (Glaser and Strauss 1967) research approach
arguing that ‘all you see is data’, the categorising of most
prominent concepts identified from over 90 different sources,
the emerging categories of concepts are diverse in research
nature. Throughout the paper, the reader meets terms related
to: (1) economic potential; (2) cognitive design; (3) risk
engineering; (4) correlation effect; (5) cognitive feedback;
(6) ‘unrecognised and outdated data. These six terms are
just examples of the plethora of different terms and concepts
that emerge from our literature review on the topic of cyber
physical system architecture. We categorised these terms
and concepts, and redesigned the exiting five levels of cyber
physical system architecture—or 5C (Fig. 1).
The grounded theory method is applied to categorise
these diverse terms and concepts to the existing architec-
ture that comprises five levels of cyber physical systems
or 5C (Fig. 1). The grounded theory approach is used to
4. AI SOCIETY
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categorise these new terms and concepts, emerging form
the literature review, and organised into cascading hierar-
chies of actions (in Table 1), presented as summary maps.
The importance of these diverse concepts and the rela-
tionship between seemingly unrelated concepts, is what
coheres to the design of the proposed hierarchical cascad-
ing approach (in Fig. 2).
The complexity of the literature coherent design becomes
more explicit with examples that are presented throughout
the paper. The examples place the paper within the expe-
riential and cultural practice of engineering. Here we pre-
sent one explicit example of how the research questions that
are drawn from the literature review are then included to
drive new finding and contributions on the identified gaps
in existing literature. The first example is used to drive con-
ceptual and theoretical underpinnings of the research gap.
This example from literature derives findings that the exact
economic impact of cognitive CPS infrastructure remains
to be determined (Leitão et al. 2016) although cognitive
CPS systems will represent a large percentage of future ICT
application in industry (Marwedel and Engel 2016). This
situation presented in this example requires a new approach
for integrating the physical and cyber subsystems of cogni-
tive CPS. The new approach needs to provide an overall
understanding of the design, development, and evolution of
cognition in CPS, and needs to integrate theories of artificial
intelligence, control of physical systems, as well as their
interaction with humans.
Such approach is especially needed for not only develop-
ing nations that lack an I4.0 strategies, but also for more
developed countries—such as the UK and USA. The UK has
been ranked as the overall global cyber superpower followed
by the US (Allen and Hamilton 2014). It is also reported that
the UK and US are strongly protected to withstand digital
infrastructure cyber-attacks, which is crucial in developing a
resilient digital economy. However, in the index quantifying
industrial applications in digital infrastructure key sectors,
the UK drops down to the 5th place and the US to the 3rd
place. This seems to be partly due to the UK and US lag-
ging behind other countries in terms of harnessing economic
value from the I4.0 (Allen and Hamilton 2014). This could
be caused by the lack of cognitive abilities in the Internet of
Things (IoT) deployment (Radanliev et al. 2020a).
The literature review continues with identifying, catego-
rising and relating emerging concepts to the conceptual and
theoretical underpinnings of the arguments that cohere to the
conceptual framework design.
Fig. 1 The 5 levels cyber physical system architecture—commonly referred to as 5C architecture
5. AI SOCIETY
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3.1 Values and risks from intrusive autonomous
self‑building connected technologies (IoT, edge
computing) in cyber physical systems
One of the main drives for artificial intelligence in cyber
physical systems is value creation. Our society is driven by
social-economic values. Organisational goals are always
based on some form of values. For example, governmental
and non-governmental sectors are driven by the development
of societal values. Private organisations are often driven by
economic values. One of the main drives for value creation
is the emerging new data streams that enable understand-
ing of new events in real-time, and predicting future events.
This new and emerging data come at volumes that only
AI can process with low-latency. Since this value emerges
from cyber physical systems, it becomes inevitable that
autonomous AI will evolve in economic and societal deci-
sion making.
This process is already in motion, triggered by the enor-
mous economic potential for hyper-connected economy.
Literature recognises that important future business oppor-
tunities lay in the networking potential of digital economy
(Nicolescu et al. 2018). The infrastructure for smart man-
ufacturing technology could create large cost savings for
manufacturers (Anderson 2016) and enable faster develop-
ment of economies of scale (Brettel et al. 2016). Industrial
Internet, or ‘Industry 4.0,’ supports a finer granularity and
control to meet individual customer requirements, creates
value opportunities (Hermann et al. 2016; Shafiq et al.
2015; Stock and Seliger 2016; Wang et al. 2016), increases
resource productivity, and provides flexibility in business
processes (Hussain 2017). The integration of cognitive
cyber-physical capabilities into IIoT arguably requires a
new process for integrating physical and cyber subsystems—
including an overall understanding of the cognitive design,
development, and evolution of CPS and IIoT. Gaining such
understanding may require consolidation of IIoT theories
for control of physical systems and the interaction between
humans and CPS (Marwedel and Engel 2016; Roure et al.
2019; Banks 2019).
On the other hand, the US National Institute of Stand-
ards and Technology (US NIST) deliberately stays away
from formalising any process model in this space (Barrett
et al. 2017; NIST 2018). Instead, their recent Framework
for Cyber Physical Systems proposes sets of artefacts and
activities that could be considered by organisations in the
deployment of CPS. These proposals are the result of formal
ontologies of digital artefacts and their interactions with the
exterior world. The US NIST identifies three main views on
CPS that encompass identified responsibilities in the sys-
tems engineering process: conceptualisation, realisation, and
assurance. Each of these three views corresponds to funda-
mental processes in the life of cognitive CPS, respectively:
(1) Models of CPS (design), (2) the CPS itself (implemen-
tation), and (3) CPS Assurance (validation). The trade-offs
between different instantiations of these processes as well
as between critical aspects such as Security, Safety, Busi-
ness, and Privacy need to be understood. In this context,
Risk Engineering is proposed as an activity embedded in
the design, development, and lifecycle of the future CPS
and IoT systems (Radanliev et al. 2020b). This assumes that
cyber risk is just one instantiation of risk for an organisation
or product and, therefore, should be subject to the higher
processes of compliance and regulation in each domain.
Building on this understanding of risk, a cognitive feedback
approach is needed for formalising compositional ways to
reason about cyber risks in an I4.0 context. For example,
what we could do to understand and measure the systemic
IIoT risk is to create a requirement for automatic sharing of
Table 1 Summary map—table of technologies that drive artificial
cognition in CPS
Taxonomy of key elements that drive AI
CPS—cognitive communities
Cyber physical systems CPS
Internet of everything IoE
5 level CPS architecture 5C
Agent-oriented architecture AoA
Object-oriented architecture OoA
Cloud optimised virtual object architecture VOA
Virtual engineering objects VEO
Virtual engineering processes VEP
Model-driven manufacturing systems MDMS
Service oriented architecture SoA
Dynamic intelligent swamps DIS
CPS—cognitive processes
Connected devices and networks CDN
Compiling for advanced analytics CfAA
Business processes and services BPS
Cloud distributed process planning DPP
Physical and human networks PHN
CPS—cognitive societies
Internet of things IoT
Web of things WoT
Social manufacturing SM
Internet of people IoP
Internet of services IoS
Systems of systems SoS
CPS—cognitive platforms
Internet protocol version 6 IPv6
Internet-based system and service platforms ISP
Model-based development platforms MBDP
Knowledge development and applications KDoA
Real-time distribution RtD
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cyber-attacks data records between IIoT supply chains. If
IoT connected devices are reporting the standalone risks of
a sole company, this would enable supply chain participants
to understand and differentiate between stand alone and sys-
temic cyber risk. However, when IoT connected devices start
reporting on standalone risks of a sole company, this could
create duplicate data records, collection of irrelevant data
records, and many other complications. Hence, the cyber-
attack reporting needs to include an element of cognition,
possibly in the fog computing layer, because it would be
challenging to implement cognition in the edge computing
systems.
3.2 Argument for cognitive analytics
The arguments for cognitive feedback approach emerge from
the inherent risk in integrating the physical with the cyber
world, where cyber risk environment is constantly changing
(Radanliev et al. 2018), and estimated loss of cybercrime
varies greatly (Biener et al. 2014; DiMase et al. 2015). The
real impact of cyber risk remains unknown (Shackelford
2016), mainly due to lack of suitable probabilistic data and
lack of a universal, standardised impact assessment frame-
work (Radanliev et al. 2020b; Koch and Rodosek 2016). To
develop such a framework, accumulated risk needs to be
quantified in real-time and shared across technology plat-
forms (Ruan 2017). This requires a dynamic understand-
ing of the network risk. In addition, new risk elements that
require cognitive analytics also need to be quantified, such
as intellectual property of digital information (Anthonysamy
et al. 2017) and the impact of media coverage (Tanczer et al.
2018).
3.3 Review on existing cyber risk analytics
The Cyber Value at Risk (CvaR) model (World Economic
Forum 2015), represents an attempt to understand the eco-
nomic impact of cyber risk for individual organisations.
CVaR provides cyber risk measurement units, value anal-
ysis methods related to the cost of different cyber-attacks
type (Roumani et al. 2016), and proof of concept methods
that are based on data assumptions. Given the lack of data
needed to validate the CvaR model, these studies calculate
the economic impact based on organisations’ ‘stand-alone’
cyber risk and, therefore, ignore the correlation effect of
sharing infrastructure and information and the probability
of cascading impacts, which represents a crucial element
of I4.0. These limitations of the CvaR model are of great
concern, e.g. in sharing cyber risk in critical infrastructure
(Zhu et al. 2011). Critical infrastructures are vital for strong
digital economies, but issues of synchrony, components fail-
ures, and increasing complexity demand development and
elaboration of new rigorous CPS methods (Rajkumar et al.
2010). In the absence of a common reference point of cyber
risks, existing cyber risk assessment methodologies have led
to inconsistencies in measuring risk (Agyepong et al. 2019),
which negatively affects the adaptation of I4.0. Assessment
of IIoT cyber risk in I4.0 should be based on a system that
enables cognitive assessment of the cyber network risk, not
only the stand-alone cyber risks (Craggs and Rashid 2017)
of a sole company (Radanliev 2014).
Fig. 2 Hierarchical cascading framework design, describing how artificial intelligence is evolving in CPS
7. AI SOCIETY
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3.4 Review of financial assessment of cyber risk
from CPS
In early literature, existing financial models have been pro-
posed to assess information security investment (Anderson
and Moore 2006; Gordon and Loeb 2002; Rodewald and
Gus 2005). However, cyber risk covers more elements than
information security financial cost, such as brand reputation
(Lee et al. 2019a) or intellectual property (Lee et al. 2019b).
In terms of modelled economic and financial impact of mas-
sive cyber-attacks, additional questions emerge in relation
to the impact on public sector, rethinking of business pro-
cesses, growth in liability risk, and mitigation options (Ruf-
fle et al. 2014). Such economic evaluations trigger a debate
between limited economic lifespans of digital assets and
value in inheriting ‘out of date’ data (Tan et al. 2008). In
an I4.0 context, cyber risks are not only simply associated
with machines and products that store their knowledge and
create a virtual living representation in the network (Drath
and Horch 2014) but also to the global flows and markets
they are part of.
4 Taxonomy of management technologies
and methodologies on AI‑enabled
methods
This section redefines the Fig. 1—5C architecture (5 lev-
els of CPS architecture) and creates a taxonomy from the
chapter 3—literature review. The taxonomy represents a
list of focal points, listed in a summary table (Table 1), for
visualising and focusing the direction for a new CPS archi-
tecture. To define the contribution from this study, before
we present the new cognitive feedback mechanism, we first
explain the existing 5C architecture in Fig. 1 as described
in (Lee et al. 2015). The purpose of including Fig. 1 was to
discuss the weaknesses of the current understanding of CPS
architecture.
From Fig. 1, we can see that the current five levels cyber
physical system architecture (5C) includes one level for
cyber elements. With the rise of connected devices—IoT
and IIoT, and AI in human–computer interactions, the cyber
level is obsolete, because each level contains various cyber
elements. In this study, we seek for improved understanding
of CPS architecture and we seek that though a taxonomy of
recent literature.
The new cognitive feedback mechanism builds upon the
existing recommendations that CPS needs to adapt quickly
(Niggemann et al. 2015), to create multi-vendor and modular
production systems (Weyer et al. 2015). Requiring under-
standing of multi-discipline testing (Balaji et al. 2015), sys-
tem sociology (Dombrowski and Wagner 2014), and social
networks (Wan et al. 2015; Roure et al. 2015).
4.1 Key technologies for self‑adapting system
Before conducting the taxonomic categorisations
in the summary tables (see chapter 5) in this final sec-
tion we compress the rationale for the categorisations
(see Table 1). This section also details the four categories,
which is one less category than the five levels of CPS pre-
sented in Fig. 1. Our CPS architecture does not include the
‘cyber’ level, which was considered as a separate level in
the previous architecture. We argue that cyber is far more
than an individual level: we argue that cyber is part of all
levels of the CPS architecture.
The academic literature we analysed outlines the evo-
lution of CPS into the more inclusive and encompassing
system that brings together people, process, data, and
things—making networked connections and transactions
more valuable to individuals, organisations, and things.
Hence, by applying grounded theory for categorising
the literature analysed, the following key feedback man-
agement technologies predominated: (a) integration of
physical flows, information flows, and financial flows; (b)
innovative approaches to managing operational processes;
(c) exploiting the industrial digitisation to gain competi-
tiveness; (d) and utilisation of Big Data to improve the
efficiency of production and services. From the extensive
literature reviewed on this topic, the requirements for
cognitive feedback are categorised in Table 1 as: follows
domain communities, processes, societies, and platforms.
These domains represent how the changing roles of inno-
vation, production, logistics, and the service processes
require CPS advancements in the following: (a) domain
communities; (b) internet-based system and service
platforms; (c) business processes and services, and (d)
dynamic real-time data from physical and human networks
(perceived as data from intelligent swamps). This intro-
duces the approach used for the taxonomic categorisations
and the summary tables in chapter 5.
5 Summary of the taxonomic analysis:
building summary maps
Although we described the process in the previous section,
we wanted to explain further that this section—chapter 5—
is summarising the findings from the literature review in
chapter 4 and categorises the emerging terms and con-
cepts into actions and activities, presented as hierarchical
cascades of activities in a summary map (Table 1). The
summary map in Table 1 is the first step in building a
new theory and improving the current five levels of CPS
architecture with a new and more up-to-date architecture.
Before presenting the summary map, we briefly discuss
8. AI SOCIETY
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the categorisations as described in the previous section
(domain communities, processes, societies, and plat-
forms.) and refer to their origin—with references from
the literature review.
5.1 Taxonomic categorisations for advancing
the existing 5C architecture
The domain communities, processes, societies, and plat-
forms, are expanded into (1) domain communities; (2)
internet-based system and service platforms; (3) business
processes and services, and (4) dynamic real-time data from
physical and human networks.
Domain communities include the following: Agent-ori-
ented Architecture (Ribeiro et al. 2010), Object-oriented
Architecture (Thramboulidis 2015), Cloud optimised Vir-
tual Object Architecture (Giordano et al. 2016), supported
with Virtual Engineering Objects and Virtual Engineering
Processes with Internet Protocol version 6 (IPv6) connected
devices and networks (Wahlster et al. 2013).
Internet-based system and service platforms (La and Kim
2010) are used to model CPS through the Web of Things
(Dillon et al. 2011), with compiling of data, processes,
devices, and systems for cognitive analytics and connection
to cognitive model-driven (robot-in-the-loop) manufactur-
ing systems (Jensen et al. 2011; Shi et al. 2011; Wang et al.
2014). Internet-based system and service platforms can be
used to promote model-based development platforms, such
as behaviour modelling of robotic systems, e.g. Automata
(Ringert et al. 2015). Internet-based systems and service
platforms can enable the development of social manufac-
turing and interconnect with the Internet of People to create
CPS collaborative communities (Lee et al. 2014).
Business processes and services need to be intercon-
nected into industrial value chains to integrate machine
information into decision making and be connected to the
Internet of Services for service oriented CPS architecture
(Wang et al. 2015) and Cloud distributed planning manu-
facturing. Business processes and services in CPS can also
promote knowledge development of business areas and
applications.
Dynamic real-time data from physical and human net-
works (perceived as dynamic intelligent swamps) of modules
connected to physical and human networks, can operate as
systems of systems, and can act as mechanisms for real-time
distribution (Kang et al. 2012) and feedback directly from
users and markets.
5.2 Summary map of emerging terms
and concepts—presented as actions
and activities
The categories of key elements for artificial cognition in
CPS are presented in Table 1. The relationships of these
elements to CPS is grouped with the grounded theory into
the following categories: CPS—cognitive communities,
CPS—cognitive processes, CPS—cognitive societies and
CPS—cognitive platforms. These categories and the syn-
ergies between the elements lead to artificial cognition in
CPS for self-aware process are categorised in Table 1. The
taxonomic analysis of the literature reviewed is applied to
structure closely related concepts higher and looser rela-
tionships lower within each category in the Table 1 sum-
mary maps. These communities, processes, societies, and
platforms emerged from categorising the literature review
findings. The taxonomic interpretation of the relationships
between these concepts is built upon the literature findings
and represent the backbone of theoretical development and
its understanding of interconnected concepts in this paper.
We created the taxonomic categorisations in Table 1 to seek
improvement and update of the existing CPS architecture
(see Fig. 1). In the taxonomy, we relate the merging concepts
to the original concept in Fig. 1, but we do not include the
‘cyber’ layer. We considered cyber to be an integral part
of all layers in CPS architecture. Hence, the taxonomy in
Table 1 contains four levels of CPS architecture.
In brief, the summary table (Table 1) can also be seen as
multiple cascading hierarchies of actions—found in litera-
ture as terms and concepts. The six terms mentioned in the
introduction of chapter 3—literature review, are dissected in
greater detail, with more specific focus on presenting actions
and activities, not desired objectives. For example, from the
six terms, we used the first term ‘(1) economic potential;’
and in the literature review, we investigated for actions and
activities that are related to this term. In the summary table
(Table 1), we can see new terms and concepts, e.g. Busi-
ness processes and services; Model-driven manufacturing
systems; etc. The wording in these terms and concepts is
structured in a more actionable form. For example, the term
(1) ‘economic potential’ does not provide any guidance on
how this economic potential can be achieved. We just dis-
covered that ‘economic potential’ was strongly present in
literature on cyber physical system architecture. So we used
this term as one of the six guidance terms in the introduction
of chapter 3. But in the summary table (Table 1), we can see
these terms as actionable concepts, e.g. ‘Model-driven man-
ufacturing systems’ that explain what needs to be done to
reach the ‘economic potential’. The summary table (Table 1)
presents multiple cascading hierarchies of actions that are
used in the design of the cascading hierarchy framework in
(in Fig. 2). Instead of presenting these actions and activities
9. AI SOCIETY
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as categories related to the six terms, we used the recom-
mendations from the literature where we found the related
actions and activities. We wanted to determine if these six
terms are true representation of all the terms and concepts in
literature, or was a different structure more relevant.
The summary maps in Table 1 confirm that a notion of
artificial cognition in CPS goes beyond machine to machine
(M2M) (Wan et al. 2013; Stojmenovic 2014), and beyond
the proposed 3 level CPS, which are (1) services, (2) cloud,
and (3) physical object layers. Artificial cognition in CPS
also goes beyond the existing knowledge of 5C architec-
ture (as seen in Fig. 1). When artificial cognition in CPS is
combined with intelligent manufacturing equipment (Posada
et al. 2015), then a new set of communities, processes, socie-
ties, and platforms (categorised in Table 1) emerge. When
combined, these new machineries represent intrusive self-
building technologies, triggering an inevitable and autono-
mous evolution of artificial cognition in CPS.
This evolution goes beyond the existing description of
5C architecture (in Fig. 1). The new description of artifi-
cial cognition in CPS (as seen in Table 1) is based on the
integration of artificial intelligence (AI), machine learning,
the cloud, and IoT, creating systems of machines capable of
interacting with humans (Carruthers 2014). For example,
the application of behaviour economics into CPS already
enables market speculation on human behaviour (Rutter
2015), and even neuromarketing (Lewis and Brigder 2004),
to determine consumer purchasing behaviour. We can expect
to see autonomous CPS adopting the use of these methods
to predetermine human behaviour.
Technologies described in Table 1 that would enable arti-
ficial cognition in CPS include software defined networks
(Kirkpatrick 2013) and software-defined storage (Ouyang
et al. 2014), built upon the following: protocols and enter-
prise grade cloud hosting; AI, machine learning, and data
analytics (Kambatla et al. 2014; Pan et al. 2015); and mesh
networks and peer-to-peer connectivity (Wark et al. 2007).
Without cognitive risk analytics, the embedded control of
CPS is creating security and risk management vulnerabilities
from integrating less secured systems, triggering questions
regarding risk management and liability for breaches and
damages (Boyes et al. 2018). Without cognitive risk analyt-
ics, many other technical challenges can be foreseen in the
CPS vital domains—especially in the design, construction,
and verification of CPS (Anthi et al. 2019).
6 From summary maps to conceptual
framework
In this section, we use the hierarchical cascading method,
with categorical coding (Radanliev 2014), to build a concep-
tual framework based on the findings in the summary map
Table 1. Our aim was not to confirm that the embodiment of
AI in the IIoT is leading to a transformation in AI; we con-
sider that as a given—postulate from the beginning of this
study. Our aim in this section was to present advancement
to the current 5 levels CPS architecture (5C) as presented
in Fig. 1 and to integrate the plethora of emerging concepts
from our literature review, which are not included in the
current 5C architecture—(in Fig. 1).
The summary maps in Table 1 should be seen from a
conceptual standpoint, and not from engineering perspective
on the definition of terms. If seen on a standalone bases, the
summary maps in Table 1 could be seen as concepts that rep-
resent a diverse set of different terms. From reading the sum-
mary maps categorisations in Table 1, the Internet Protocol
v6 is categorised as a platform, while from an engineering
perspective IPv6 is a networking protocol. There are mul-
tiple categorisations of this type. To reduce the categories
and themes in our pursuit of deeper understanding of these
categories, the grounded theory approach used the Pugh-
controlled convergence and, in the process, themes are asso-
ciated with the ‘best fit’ categories. The rationale for this cat-
egorisation is as follows: Protocol (e.g. the Internet Protocol
v6) is the official procedure or system of rules governing the
communication or activities of programs and/or industries.
Platform on the other hand refers to the technologies that
are used as a base upon which other applications, processes
or technologies are developed. A CPS in the context of this
categorisation is a platform, while the languages it uses to
communicate (e.g. IPv6) with software are the protocol.
Further clarification as why such categorisations have
been made by applying the Pugh-controlled convergence to
reduce the number of categories is that we can consider a
platform as a software, while protocol is more like a theory,
or theoretical model which a platform can be based on. In
the interest of keeping the cascading hierarchy design to a
level that can easily be understood, the presented categorisa-
tions have been associated in abbreviated form in Table 2.
Table 2 Emerging 4 levels CPS architecture
Artificial cognition in CPS
CPS—cog-
nitive com-
munities
CPS—
cognitive
processes
CPS—cognitive societies CPS—
cognitive
platforms
5C: AoA,
OoA,
VOA,
VEO,
VEP
CDN IoT IPv6
MDMS CfAA WoT, SM, IoP ISP, MBDP
SoA BPS, DPP IoS KDoA
DIS PHN SoS RtD
10. AI SOCIETY
1 3
The cascading hierarchy design in Table 2 represents
the first step in the conceptual framework design in Fig. 2.
The similarities between Table 2 and Fig. 2 are clear. The
differences between the new understanding of artificial
intelligence in CPS in Fig. 2 are also clear and very dis-
tinguishable from the existing understanding of artificial
intelligence in CPS as seen in Fig. 1. Our approach for
building the conceptual framework (Fig. 2) is based on
an extensive review of literature that included multiple
systems, models, and methodologies from over 90 leading
articles on this topic. Concepts that reappeared in multiple
articles were selected as the most prominent, and the rela-
tionships were recorded from each article. This enables a
new approach to building the conceptual framework, based
on complex socio-economic, organisation goals and policy
issues that were identified in over 90 leading articles in
this field, published in the past decade.
The taxonomy of abbreviations in Table 2 was derived
from the taxonomy of literature in Table 1, which catego-
rises the emerging concepts into a structure for artificial
cognition in CPS. The structure relates the cognition in
CPS with IIoT, bringing together the IoP and IoS, along
with the process and transaction of IoT data. For example,
the IoT data from DIS (see Tables 1 and 2 for definitions
of abbreviations) connected to IoP and IoS, (representing
systems of systems) enhance the cyber risk avoidance with
real-time distribution and feedback directly from users and
markets.
Thus, the evolution of cognition in CPS space adds a new
perspective to the existing cyber risk avoidance mechanisms.
The inter-relationships between these elements are crucial
for defining dynamic cyber risk analytics with real-time
probabilistic data. The current approaches taken for cyber
risk analytics assume development of IoP and IoS and reli-
ability of IoT. A deeper understanding of the relationship
between IoT and I4.0, following the categories presented in
Table 1, is required to develop a dynamic cyber risk analyt-
ics structure.
Furthermore, Table 2 shows that cognitive CPS capa-
bilities are related to the integration of cyber physical
capabilities into the industrial value chains. Hence, the
proposed structure for cognitive CPS uses principles of
IoT and integrates network intelligence, providing conver-
gence, orchestration, and visibility across otherwise dis-
parate systems. The proposed cognitive CPS also provides
a structure for the operation and management of multi-
ple CPS-related elements in the context of I4.0. Figure 2
shows the inter-relationship between different cognitive
CPS communities, processes, societies, and platforms. The
integration of cyber physical capabilities into the cognitive
CPS involves the integration of IoT, WoT, SM, IoP, and
IoS into SoS. With the use of Grounded Theory and Pugh-
controlled convergence, the categories (from Table 1) are
correlated in a hierarchical framework in Fig. 2, and cor-
respond with the taxonomy (in Table 2). These are estab-
lished models for decomposing and reverse engineering
design processes. The hierarchical cascading in Fig. 2
explores the potential for automated and semi-automated
methods that could be applied to ascertain and accelerate
(and start to automate) the evolution of autonomous arti-
ficial intelligence in CPS. The concepts and the hierarchi-
cal structure in Fig. 2 originate from the summary map
and the hierarchical cascading of actions in Table 1. The
abbreviations are present in Table 1, and categorisation
of taxonomic imperatives is first presented in Table 2. In
Fig. 2, we apply the findings to build a conceptual diagram
for visualising the updated CPS architecture.
The conceptual diagram in Fig. 2 originates from the
re-evaluated five levels in the original 5C architecture,
but without the ‘cyber’ level—described in Fig. 1. The
remaining four levels are updated with concepts emerg-
ing from recent literature on this topic, with a time span
between 2010 and 2020. We identified from literature (in
the summary map Table 1) new and emerging concepts
related to CPS architecture that are not included in the
current 5C architecture. In Fig. 2, we present a hierarchi-
cal integration of these new and emerging concepts and
present an updated 4C architecture—four levels of CPS
architecture.
Since this review paper is built upon the notion of
updating the existing 5C architecture in Fig. 1, we used
the same conceptual order, but we integrated the improve-
ments found in recent literature. We identified a lot of
new terms, springing up between 2010 and 2020, and we
wanted to put them in conceptual order. We anticipated
this to be a required first step and a real service to future
studies aiming to build a diagnostic architecture. The
conceptual diagram in Fig. 2 derives new understanding
on why cognitive evolution in cyber physical systems is
inevitable and autonomous with the increased integration
of connected devices (IoT). The hierarchical cascading in
Fig. 2 is designed using the grounded theory approach for
relating emerging concepts. The emerging concepts identi-
fied in the literature review are first presented in the sum-
mary maps, and then taxonomic approach is used to relate
the categories and organise in a hierarchy of most closely
to most distantly related. Conceptual design is then used
to cascade the hierarchy in a framework. The framework in
Fig. 2 explores how automated and semi-automated meth-
ods are accelerating (starting to automate) the evolution of
autonomous artificial intelligence in CPSs. The framework
in Fig. 2 represents a new mechanism and prototype of a
hierarchical structure that facilitates deeper understanding
of interconnected concepts—both being crucial given that
there is no direct reference in literature to artificial cogni-
tion in CPS and cyber risk analytics.
11. AI SOCIETY
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For final comparison, we present a visualisation in Fig. 3
that compares the emerging four levels of CPS architecture.
In Fig. 3, we can see that CPS as a concepts has evolved
significantly since the 5 levels CPS architecture in Fig. 1.
In Fig. 3, we can see how the taxonomy from the sum-
mary map in Table 1 has been integrated in the four levels
CPS architecture. We can also compare Figs. 1 and 3 to
visualise the differences between the CPS architectures from
2015 and 2020. Although Fig. 2 presents the same informa-
tion, in a conceptual diagram, we designed Fig. 3 for easier
comparison.
7 Discussion
The updated four levels—CPS architecture in Fig. 2 offers
a new and important step in updating our understanding of
how CPS operate in 2020. Since the existing 5 levels CPS
architecture (see Fig. 1) is few years old, and there has been
many changes in connected systems since its creation, we
considered this update timely and of relevance. We also
argue that with the rise in new IoT and IIoT, complex, cou-
pled and connected systems, such updates should occur at
much faster intervals. This paper adopted the argument that
AI should ‘be programmed with a virtual consciousness and
conscience’ (Meissner 2020), because we are in the middle
of a new AI revolution that is changing our economy and
society. There are studies investigating whether AI can cre-
ate ‘novel though’ (Fazi 2019). The mechanism in this paper
describing how AI is evolving into CPS is based on grouping
of future and present techniques and presenting the design
process through a new hierarchical cascading design for a
conceptual framework.
The conceptual framework in Fig. 2 details significant
advancements over the past 5 years that can be seen in the
most closely related framework on this topic in Fig. 1. For
example, cognition in Fig. 1 is based solely on decision
support system for prioritising workload, with a single focus
on industrial processes. The new conceptual framework pre-
sented in Fig. 2 includes social machines, connected devices,
and knowledge developments, among new concepts such as
internet of services and internet of people.
The differences between the new framework in Fig. 2 and
the earlier framework as seen in Fig. 1 mean that AI is evolv-
ing at a much faster rate than industrial understanding of this
process. The new framework in Fig. 2 captures the changes
in connected devices generating vast amounts of data, cap-
tured and stored in different heterogenous formats (e.g.
high-dimensional data, real-time data, translytic data, spa-
tiotemporal data). The new framework in Fig. 2 details the
process of how the new data are captured, stored, processed,
analysed, and used in near real-time, with low-latency. This
is a very different process than our past understanding of
CPS cognitive decision-making tasks, as seen in Fig. 1.
The main point of discussion from the new conceptual
framework is that CPS are capable of much more than we
describe in existing frameworks on CPS cognition in Fig. 1.
With the availability of new types of data from IoT devices,
CPS are becoming more automated. For example, with the
new translytic data, CPS can transact and analyse data. With
spatiotemporal data, CPS can map the demand in real-time.
And with the complexities of high-dimensional data, CPS
can understand the relationships between seemingly unre-
lated events and create new services and products. These
new data streams are highly complex, and only AI can
analyse such data and derive predictions with low-latency.
Hence the evolution of AI in CPS is inevitable, autonomous,
and it is already happening.
The arguments presented in this research are focused
on understanding how the increased computational power
of connected devices, has created intrusive self-building
CPS, that represent human-like performance, triggering the
creation of collective intelligence. The aggregated knowl-
edge synthesised from recent literature, created a more
Fig. 3 Emerging CPS architec-
ture—4 levels
12. AI SOCIETY
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comprehensive understanding of the current evolution of
AI in CPS. We should not wait another 5 years before a new
framework is designed to explain how AI is evolving with
the emergence of new data formats, analysed with increased
computational powers in connected devices.
8 Conclusion
In this paper, we have produced a hierarchical cascading
framework for analysing the evolution of AI decision-mak-
ing in cyber physical systems. The significance of the new
framework is the findings that (1) such evolution is auton-
omous because of the increased integration of connected
devices (IoT) in cyber physical systems; (2) such evolution
is inevitable, because only AI can analyse the volume of data
generated in low-latency, near real-time, hence, only AI can
create value from new and emerging forms of big data. Nev-
ertheless, we argue that the main value of the new 4 levels of
CPS architecture, is the perception of cyber-physical systems
as physical and human networks, where cognition emerges
from the cyber-physical ‘societies’ and ‘communities’ (see
Table 1). Our interpretation of CPS architecture perceives
cyber-physical systems as social machines, and we place
value in human interaction with such systems. In previous
CPS architecture (Fig. 1), we can see that human interven-
tion is predominated in the configuration level and the CPS
depend on human cognition and there is a separate layer for
‘cyber’. In our 4 levels of CPS, we integrated the ‘cyber’
in all levels, and we argue that there is a value for artificial
intelligence to learn from human–computer interactions.
Instead of relying only on feedback from connected devices,
in some scenarios, human input is of much greater value.
We have seen this in the current efforts to monitor a fast
spreading pandemic—Covid-19. All contact tracing apps are
based on human–computer input. Relying on computer data
alone, was considered too slow and ineffective. We use this
as a final example to rationalise our argument for perceiving
future cyber-physical systems operating as social machines,
obtaining input from humans and connected devices.
To present this rationale, in the taxonomic methodology,
we adapted the summary map method, for transparency and
justifications for concept selection and we used the litera-
ture review for decisions on the design of the hierarchical
cascading. Out attempt in this paper was to contribute to the
cultural practice of engineering discussion, on how artificial
intelligence is evolving over time, by presenting a snapshot
in time on this topic. It is evident that our analysis builds on
considerable assumptions and guesses based on findings and
taxonomic categorisation of existing literature. Our discus-
sion in this paper points to the importance of understand-
ing the impact of connecting complex and coupled systems.
Complex interconnected and coupled systems can evolve
automatically with the continuous technological upgrades
in existing CPS. The new hierarchical cascading framework
in this paper identifies approaches to model imperative
mechanisms within complex interconnected and coupled
systems. In important environments for AI, such as IoT, we
can model the connections and interdependencies between
components to both external and internal IoT services and
CPS in summary map. The summary map identifies the
imperative categories for the evolution of artificial cognition
in CPS. By applying established engineering design models,
the summary map is advanced in a hierarchical structure
for artificial intelligence in CPS. However, more empirical
and philosophical research is needed on this topic before we
can argue a comprehensive understanding on how artificial
intelligence is evolving behind complex interconnected and
coupled systems.
Compliance with ethical standards
Conflict of interest On behalf of all authors, the corresponding author
states that there is no conflict nor competing interest.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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