Data-Driven Calibration of Soil Moisture Sensor Considering Impacts of Temperature : A Case Study on FDR Sensors
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Article number | 4381 |
Journal / Publication | Sensors (Switzerland) |
Volume | 19 |
Issue number | 20 |
Online published | 10 Oct 2019 |
Publication status | Published - Oct 2019 |
Externally published | Yes |
Link(s)
DOI | DOI |
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Attachment(s) | Documents
Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85073568994&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(f6486a75-d3e0-4822-8568-6791c6b4ed6e).html |
Abstract
Commercial soil moisture sensors have been widely applied into the measurement of soil moisture content. However, the accuracy of such sensors varies due to the employed techniques and working conditions. In this study, the temperature impact on the soil moisture sensor reading was firstly analyzed. Next, a pioneer study on the data-driven calibration of soil moisture sensor was investigated considering the impacts of temperature. Different data-driven models including the multivariate adaptive regression splines and the Gaussian process regression were applied into the development of the calibration method. To verify the efficacy of the proposed methods, tests on four commercial soil moisture sensors were conducted; these sensors belong to the frequency domain reflection (FDR) type. The numerical results demonstrate that the proposed methods can greatly improve the measurement accuracy for the investigated sensors.
Research Area(s)
- Calibration, Data-driven, Impacts of temperature, Soil moisture sensor
Bibliographic Note
Citation Format(s)
In: Sensors (Switzerland), Vol. 19, No. 20, 4381, 10.2019.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review