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

Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Razvan Nicolescu ◽  
Michael Huth ◽  
Omar Santos

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.

2021 ◽  
Vol 65 (1) ◽  
pp. 7-26
Author(s):  
Barbara Siuta-Tokarska ◽  

This paper discusses the problems connected with visible changes in industry in the context of the consequent four industrial revolutions. The last one is associated with “industry 4.0”, which in turn manifests in the presence of the following constitutive parts (systems): cyber physical systems, the Internet of Things, the Internet of Services and intelligent factories. Another important factor of the ongoing changes is the appearance of a new branch, which tries to comprise in its theoretical divagations the problems discussed in IT, mathematics, neurophysiology, electronics, psychology, anthropology and philosophy. In the experimental area this realm, in turn, is treated as a branch of IT. All these constituents can be defined as artificial intelligence. The aim of this research is an attempt to answer the question posed in the title of the article, taking into consideration the potentially most holistic approach to these problems in the context of sustainable development of the constituent capitals taking into consideration not only the increasing of opportunities but maximizing the benefits in the natural, social and economic spheres.


2021 ◽  
Vol 113 (7-8) ◽  
pp. 2395-2412
Author(s):  
Baudouin Dafflon ◽  
Nejib Moalla ◽  
Yacine Ouzrout

AbstractThis work aims to review literature related to the latest cyber-physical systems (CPS) for manufacturing in the revolutionary Industry 4.0 for a comprehensive understanding of the challenges, approaches, and used techniques in this domain. Different published studies on CPS for manufacturing in Industry 4.0 paradigms through 2010 to 2019 were searched and summarized. We, then, analyzed the studies at a different granularity level inspecting the title, abstract, and full text to include in the prospective study list. Out of 626 primarily extracted relevant articles, we scrutinized 78 articles as the prospective studies on CPS for manufacturing in Industry 4.0. First, we analyzed the articles’ context to identify the major components along with their associated fine-grained constituents of Industry 4.0. Then, we reviewed different studies through a number of synthesized matrices to narrate the challenges, approaches, and used techniques as the key-enablers of the CPS for manufacturing in Industry 4.0. Although the key technologies of Industry 4.0 are the CPS, Internet of Things (IoT), and Internet of Services (IoS), the human component (HC), cyber component (CC), physical component (PC), and their HC-CC, CC-PC, and HC-PC interfaces need to be standardized to achieve the success of Industry 4.0.


Author(s):  
Kadir Alpaslan Demir ◽  
Buğra Turan

The introduction of Industry 4.0 has increased the focus on a number of technologies. These technologies also help realize the vision for intelligent cities. Furthermore, there are already discussions of Industry 5.0. One emerging aspect of Industry 5.0 is human-robot co-working. With the help of artificial intelligence, the internet of things paradigm, Industry 4.0, and Industry 5.0 visions, there will be two predominant types of systems interfacing with people in intelligent cities. These are robotic and ambient intelligence systems. The increasing deployment of these will help make cities even smarter. However, we need to see advancements in a number of relevant key technologies, including power and networking technologies. In this chapter, first, the authors briefly discuss Industry 4.0, Industry 5.0, and intelligent cities paradigm, as well as robotic and ambient intelligence systems. Then, they focus on developing trends in power and networking technologies.


Author(s):  
Anna Smyshlyaeva ◽  
Kseniya Reznikova ◽  
Denis Savchenko

With the advent of the Industry 4.0 concept, the approach to production automation has fundamentally changed. The manufacturing industry is based on such modern technologies as the Internet of Things, Big Data, cloud computing, artificial intelligence and cyber-physical systems. These technologies have proven themselves not only in industry, but also in various other branches of life. In this paper, the authors consider the concept of cyber-physical systems – systems based on the interaction of physical processes with computational ones. The article presents a conceptual model of cyber-physical systems that displays its elements and their interaction. In cyber-physical systems, it represents five levels: physical, network, data storage, processing and analytics level, application level. Cyber-physical systems carry out their work using a basic set of technologies: the Internet of things, big data and cloud computing. Additional technologies are used depending on the purpose of the system. At the physical level, data is collected from physical devices. With the help of the Internet of Things at the network level, data is transferred to a data warehouse for further processing or processed almost immediately thanks to cloud computing. The amount of data in cyber-physical systems is enormous, so it is necessary to use big data technology and effective methods for processing and analyzing this data. The main feature of this technological complex is real-time operation. Despite the improvement in the quality of production and human life, cyber-physical systems have a number of disadvantages. The authors highlight the main problems of cyber-physical systems and promising areas of research for their development. Having solved the listed problems, cyber-physical systems will reach a qualitatively new level of utility. The paper also provides examples of the implementation of concepts such as a smart city, smart grid, smart manufacturing, smart house. These concepts are based on the principle of cyber-physical systems.


2021 ◽  
Vol 58 ◽  
pp. 176-192
Author(s):  
Diego G.S. Pivoto ◽  
Luiz F.F. de Almeida ◽  
Rodrigo da Rosa Righi ◽  
Joel J.P.C. Rodrigues ◽  
Alexandre Baratella Lugli ◽  
...  

2018 ◽  
Vol 15 (4) ◽  
pp. 528-534
Author(s):  
Adriano Pereira ◽  
Eugênio De Oliveira Simonetto ◽  
Goran Putnik ◽  
Helio Cristiano Gomes Alves de Castro

Technological evolutions lead to changes in production processes; the Fourth Industrial Revolution has been called Industry 4.0, as it integrates Cyber-Physical Systems and the Internet of Things into supply chains. Large complex networks are the core structure of Industry 4.0: any node in a network can demand a task, which can be answered by one node or a set of them, collaboratively, when they are connected. In this paper, the aim is to verify how (i) network's connectivity (average degree) and (ii) the number of levels covered in nodes search impacts the total of production tasks completely performed in the network. To achieve the goal of this paper, two hypotheses were formulated and tested in a computer simulation environment developed based on a modeling and simulation study. Results showed that the higher the network's average degree is (their nodes are more connected), the greater are the number of tasks performed; in addition, generally, the greater are the levels defined in the search for nodes, the more tasks are completely executed. This paper's main limitations are related to the simulation process, which led to a simplification of production process. The results found can be applied in several Industry 4.0 networks, such as additive manufacturing and collaborative networks, and this paper is original due to the use of simulation to test this kind of hypotheses in an Industry 4.0 production network.


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