Introduction to the special section on application of artificial intelligence in security of cyber physical systems (VSI-aicps)

Artificial Intelligence and the Internet of Things in Industry 4.0

CCF Transactions on Pervasive Computing and Interaction ◽

10.1007/s42486-021-00057-3 ◽

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.

Download Full-text

Introduction to the Special Section on Data Science for Cyber-Physical Systems

ACM Transactions on Internet Technology ◽

10.1145/3464766 ◽

2021 ◽

Vol 21 (2) ◽

pp. 1-7

Author(s):

Francesco Piccialli ◽

Nik Bessis ◽

Gwanggil Jeon ◽

Calton Pu

Keyword(s):

Data Science ◽

Special Section ◽

Cyber Physical Systems ◽

Physical Systems

Download Full-text

Towards Sustainable Models of Computation for Artificial Intelligence in Cyber-Physical Systems

10.1109/iecon48115.2021.9589594 ◽

2021 ◽

Author(s):

Massimiliano Pirani ◽

Aldo Franco Dragoni ◽

Sauro Longhi

Keyword(s):

Artificial Intelligence ◽

Cyber Physical Systems ◽

Models Of Computation ◽

Physical Systems

Download Full-text

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

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Artificial Intelligence Paradigms for Smart Cyber-Physical Systems ◽

10.4018/978-1-7998-5101-1.ch003 ◽

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.

Download Full-text