A Combined Semi-Supervised Deep Learning Method for Oil Leak Detection in Pipelines Using IIoT at the Edge

Pipelines are integral components for storing and transporting liquid and gaseous petroleum products. Despite being durable structures, ruptures can still occur, resulting not only in financial losses and energy waste but, most importantly, in immeasurable environmental disasters and possibly in hum...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 22; no. 11; p. 4105
Main Authors:	Spandonidis, Christos, Theodoropoulos, Panayiotis, Giannopoulos, Fotis
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 28.05.2022 MDPI
Subjects:	CNN classifier deep learning edge computing leakage detection LSTM autoencoders Neural networks oil pipeline Pipelines Sensors Signal processing LSTM autoencoders oil pipeline deep learning CNN classifier leakage detection edge computing
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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