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Data-Driven Calibration of Soil Moisture Sensor Considering Impacts of Temperature: A Case Study on FDR Sensors

1
National Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China
2
Key Laboratory for Quality Testing of Hardware and Software Products on Agricultural Information, Ministry of Agriculture, Beijing 100097, China
3
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
4
Key Laboratory of Wind Energy and Solar Energy Technology (Inner Mongolia University of Technology), Ministry of Education, Hohhot 010051, China
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(20), 4381; https://doi.org/10.3390/s19204381
Received: 14 August 2019 / Revised: 19 September 2019 / Accepted: 8 October 2019 / Published: 10 October 2019
(This article belongs to the Special Issue IoT Technologies and the Agricultural Value Chain)
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.
Keywords: calibration; data-driven; impacts of temperature; soil moisture sensor calibration; data-driven; impacts of temperature; soil moisture sensor
MDPI and ACS Style

Chen, L.; Zhangzhong, L.; Zheng, W.; Yu, J.; Wang, Z.; Wang, L.; Huang, C. Data-Driven Calibration of Soil Moisture Sensor Considering Impacts of Temperature: A Case Study on FDR Sensors. Sensors 2019, 19, 4381.

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