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UAV and IoT-Based Systems for the Monitoring of Industrial Facilities Using Digital Twins: Methodology, Reliability Models, and Application.

Authors :
Sun, Yun
Fesenko, Herman
Kharchenko, Vyacheslav
Zhong, Luo
Kliushnikov, Ihor
Illiashenko, Oleg
Morozova, Olga
Sachenko, Anatoliy
Source :
Sensors (14248220). Sep2022, Vol. 22 Issue 17, p6444. 31p.
Publication Year :
2022

Abstract

This paper suggests a methodology (conception and principles) for building two-mode monitoring systems (SMs) for industrial facilities and their adjacent territories based on the application of unmanned aerial vehicle (UAV), Internet of Things (IoT), and digital twin (DT) technologies, and a set of SM reliability models considering the parameters of the channels and components. The concept of building a reliable and resilient SM is proposed. For this purpose, the von Neumann paradigm for the synthesis of reliable systems from unreliable components is developed. For complex SMs of industrial facilities, the concept covers the application of various types of redundancy (structural, version, time, and space) for basic components—sensors, means of communication, processing, and presentation—in the form of DTs for decision support systems. The research results include: the methodology for the building and general structures of UAV-, IoT-, and DT-based SMs in industrial facilities as multi-level systems; reliability models for SMs considering the applied technologies and operation modes (normal and emergency); and industrial cases of SMs for manufacture and nuclear power plants. The results obtained are the basis for further development of the theory and for practical applications of SMs in industrial facilities within the framework of the implementation and improvement of Industry 4.0 principles. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
22
Issue :
17
Database :
Academic Search Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
159033498
Full Text :
https://doi.org/10.3390/s22176444