In-situ event localization for pipeline monitoring system based wireless sensor network using K-nearest neighbors and support vector machine
Joint Authors
Hadi, Ahmad H.
Sharif, Walid F.
Source
al-Qadisiyah Journal for Computer Science and Mathematics
Issue
Vol. 12, Issue 3 (30 Sep. 2020), pp.1-15, 15 p.
Publisher
University of al-Qadisiyah College of computer Science and Information Technology
Publication Date
2020-09-30
Country of Publication
Iraq
No. of Pages
15
Main Subjects
Information Technology and Computer Science
Abstract EN
Pipeline Monitoring Systems (PMS) benefits the most of recent developments in wireless remote monitoring since each pipeline would span for long distances which make conventional methods unsuitable.
Precise monitoring and detection of damaging events requires moving large amounts of data between sensor nodes and base station for processing which require high bandwidth communication protocol.
To overcome this problem, In-Situ processing can be practiced by processing the collected data locally at each node instead of the base station.
However, this introduce a challenge to the limited resources available on the nodes.
In this paper, a Wireless Sensor Network (WSN) was implemented for In-Situ Pipeline Monitoring System with proposed algorithms for event location estimation.
The proposed algorithms include feature extraction (using ANOVA), dimensionality reduction using statistical procedure that is (Principle Component Analysis PCA) and data classification using supervised learning K-Nearest Neighbors (KNN) and Support Vector Machine (SVM).
The proposed system was tested on pipelines in Al-Mussaib Gas Turbine Power Plant.
During test, knocking events are applied at several distances relative to the nodes locations.
Data collected at each node is filtered and processed locally in real time in each two adjacent nodes.
The results of the estimation is then sent to the supervisor at base-station for display.
The results show the proposed system ability to estimate the location of knocking event.
American Psychological Association (APA)
Hadi, Ahmad H.& Sharif, Walid F.. 2020. In-situ event localization for pipeline monitoring system based wireless sensor network using K-nearest neighbors and support vector machine. al-Qadisiyah Journal for Computer Science and Mathematics،Vol. 12, no. 3, pp.1-15.
https://search.emarefa.net/detail/BIM-1266388
Modern Language Association (MLA)
Hadi, Ahmad H.& Sharif, Walid F.. In-situ event localization for pipeline monitoring system based wireless sensor network using K-nearest neighbors and support vector machine. al-Qadisiyah Journal for Computer Science and Mathematics Vol. 12, no. 3 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1266388
American Medical Association (AMA)
Hadi, Ahmad H.& Sharif, Walid F.. In-situ event localization for pipeline monitoring system based wireless sensor network using K-nearest neighbors and support vector machine. al-Qadisiyah Journal for Computer Science and Mathematics. 2020. Vol. 12, no. 3, pp.1-15.
https://search.emarefa.net/detail/BIM-1266388
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 15
Record ID
BIM-1266388