Embedded Agent based on Cyber Physical Systems: Architecture, Hardware Definition and Application in Industry 4.0 Context

2018 ◽  
Author(s):  
Mario Ricardo Nascimento Marques Junior ◽  
Braian Konzgen Maciel ◽  
Gabriel M. Balota ◽  
Renan T. Fonseca ◽  
Manuel Simosa ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Systems Architecture ◽  
Agent Based ◽  
Physical Systems

Teamwork Behavior

2019 ◽  
pp. 1-25 ◽  
Author(s):  
Paraskevi Tsoutsa ◽  
Panos Fitsilis ◽  
Omiros Ragos
Keyword(s):  
Internet Of Things ◽  
Organizational Performance ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Research Field ◽  
Important Research ◽  
Key Factors ◽  
Agent Based ◽  
Physical Systems ◽  
Advance Research

Teamwork has become an important research field and its contribution to organizational performance has attracted attention of researchers from several disciplines. The development and application of newly emerged technologies such as Industry 4.0, Internet of Things, and cyber physical systems create additional concerns for teamwork which claim to be integrated into existing models. The objective of this chapter is to advance research on teamwork, by facilitating researchers with a review which identifies the key factors that affect teamwork behavior both in human and in agent-based teamwork models, while indicating if and how they are inter-related. A review of related studies was conducted, and, as a result, a range of factors that affect teamwork behavior to both human and agent-based models was identified and analyzed. From the analysis, stand out factors that gain attention while newly-appeared factors are determined from recent studies about models shift towards dynamic and realistic environments. These discoveries point to new aspects of teamwork behavior.

scholarly journals Cyber-physical Systems Architecture for Self-Aware Machines in Industry 4.0 Environment

2015 ◽  
Vol 48 (3) ◽  
pp. 1622-1627 ◽  
Author(s):  
Behrad Bagheri ◽  
Shanhu Yang ◽  
Hung-An Kao ◽  
Jay Lee
Keyword(s):  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Systems Architecture ◽  
Physical Systems

scholarly journals The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: a literature review

2021 ◽  
Vol 113 (7-8) ◽  
pp. 2395-2412
Author(s):  
Baudouin Dafflon ◽  
Nejib Moalla ◽  
Yacine Ouzrout
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Review Literature ◽  
Comprehensive Understanding ◽  
Physical Systems ◽  
Fine Grained ◽  
Key Technologies ◽  
Granularity Level ◽  
Human Component

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.

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.

scholarly journals Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 487 ◽  
Author(s):  
Mahmoud Elsisi ◽  
Karar Mahmoud ◽  
Matti Lehtonen ◽  
Mohamed M. F. Darwish
Keyword(s):  
Machine Learning ◽  
Smart Grids ◽  
Industry 4.0 ◽  
Learning Algorithm ◽  
Cyber Physical Systems ◽  
The Internet ◽  
Smart Meters ◽  
Industrial Environment ◽  
Physical Systems ◽  
Smart Machines

The modern control infrastructure that manages and monitors the communication between the smart machines represents the most effective way to increase the efficiency of the industrial environment, such as smart grids. The cyber-physical systems utilize the embedded software and internet to connect and control the smart machines that are addressed by the internet of things (IoT). These cyber-physical systems are the basis of the fourth industrial revolution which is indexed by industry 4.0. In particular, industry 4.0 relies heavily on the IoT and smart sensors such as smart energy meters. The reliability and security represent the main challenges that face the industry 4.0 implementation. This paper introduces a new infrastructure based on machine learning to analyze and monitor the output data of the smart meters to investigate if this data is real data or fake. The fake data are due to the hacking and the inefficient meters. The industrial environment affects the efficiency of the meters by temperature, humidity, and noise signals. Furthermore, the proposed infrastructure validates the amount of data loss via communication channels and the internet connection. The decision tree is utilized as an effective machine learning algorithm to carry out both regression and classification for the meters’ data. The data monitoring is carried based on the industrial digital twins’ platform. The proposed infrastructure results provide a reliable and effective industrial decision that enhances the investments in industry 4.0.

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