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Advances in Machine Learning for Sensing and Condition Monitoring.

Authors :
Ao, Sio-Iong
Gelman, Len
Karimi, Hamid Reza
Tiboni, Monica
Source :
Applied Sciences (2076-3417); Dec2022, Vol. 12 Issue 23, p12392, 23p
Publication Year :
2022

Abstract

In order to overcome the complexities encountered in sensing devices with data collection, transmission, storage and analysis toward condition monitoring, estimation and control system purposes, machine learning algorithms have gained popularity to analyze and interpret big sensory data in modern industry. This paper put forward a comprehensive survey on the advances in the technology of machine learning algorithms and their most recent applications in the sensing and condition monitoring fields. Current case studies of developing tailor-made data mining and deep learning algorithms from practical aspects are carefully selected and discussed. The characteristics and contributions of these algorithms to the sensing and monitoring fields are elaborated. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
23
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
160713712
Full Text :
https://doi.org/10.3390/app122312392