scholarly journals Toward Intelligent Cyber-Physical Systems: Digital Twin Meets Artificial Intelligence

2021 ◽  
Vol 59 (8) ◽  
pp. 14-20
Author(s):  
Milan Groshev ◽  
Carlos Guimaraes ◽  
Jorge Martin-Perez ◽  
Antonio de la Oliva
Keyword(s):  
Artificial Intelligence ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Digital Twin

scholarly journals Artificial Intelligence and the Internet of Things in Industry 4.0

2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Razvan Nicolescu ◽  
Michael Huth ◽  
Omar Santos
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Leading Industry ◽  
Key Technologies ◽  
The Internet Of Things ◽  
State Of Art ◽  
Social Level

AbstractThis 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 perspective. 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 classifications, 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.

Validity Frame Supported Digital Twin Design of Complex Cyber-Physical Systems

2021 ◽  
Author(s):  
Bert Van Acker ◽  
Joost Mertens ◽  
Paul De Meulenaere ◽  
Joachim Denil
Keyword(s):  
Cyber Physical Systems ◽  
Twin Design ◽  
Physical Systems ◽  
Digital Twin

Explainable Artificial Intelligence (xAI) Approaches and Deep Meta-Learning Models for Cyber-Physical Systems

2021 ◽  
pp. 42-67
Author(s):  
Evren Daglarli
Keyword(s):  
Artificial Intelligence ◽  
Cyber Physical Systems ◽  
Black Box ◽  
The Internet ◽  
Learning Models ◽  
Physical Systems ◽  
Box Models ◽  
Explainable Artificial Intelligence ◽  
Meta Learning ◽  
Black Box Models

Today, the effects of promising technologies such as explainable artificial intelligence (xAI) and meta-learning (ML) on the internet of things (IoT) and the cyber-physical systems (CPS), which are important components of Industry 4.0, are increasingly intensified. However, there are important shortcomings that current deep learning models are currently inadequate. These artificial neural network based models are black box models that generalize the data transmitted to it and learn from the data. Therefore, the relational link between input and output is not observable. For these reasons, it is necessary to make serious efforts on the explanability and interpretability of black box models. In the near future, the integration of explainable artificial intelligence and meta-learning approaches to cyber-physical systems will have effects on a high level of virtualization and simulation infrastructure, real-time supply chain, cyber factories with smart machines communicating over the internet, maximizing production efficiency, analysis of service quality and competition level.

Artificial intelligence for securing industrial-based cyber–physical systems

2021 ◽  
Vol 117 ◽  
pp. 291-298
Author(s):  
Zhihan Lv ◽  
Dongliang Chen ◽  
Ranran Lou ◽  
Ammar Alazab
Keyword(s):  
Artificial Intelligence ◽  
Cyber Physical Systems ◽  
Physical Systems

scholarly journals IoT-Based Digital Twin for Energy Cyber-Physical Systems: Design and Implementation

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4762 ◽  
Author(s):  
Ahmed Saad ◽  
Samy Faddel ◽  
Osama Mohammed
Keyword(s):  
Power Systems ◽  
Systems Design ◽  
Cyber Physical Systems ◽  
Superior Performance ◽  
Physical Systems ◽  
Digital Twin ◽  
Power And Control ◽  
Amazon Web Services ◽  
High Bandwidth ◽  
And Control

With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllers’ states.

scholarly journals Artificial intelligence in cyber physical systems

AI & Society ◽  
2020 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Max Van Kleek ◽  
Omar Santos ◽  
Uchenna Ani
Keyword(s):  
Artificial Intelligence ◽  
Cyber Physical Systems ◽  
Physical Systems
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