<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Agriculture faces several challenges to use the available resources in a more environmentally sustainable manner. One of the most significant is to develop sustainable water management. The modern Internet of Things (IoT) techniques with real-time data collection and visualisation can play an important role in monitoring the readily available moisture in the soil. An automated Arduino-based low-cost capacitive soil moisture sensor has been calibrated and developed for data acquisition. A sensor- and soil-specific calibration was performed for the soil moisture sensors (SKU:SEN0193 - DFROBOT, Shanghai, China). A Repeatability and Reproducibility study was conducted by range of mean methods on clay loam, sandy loam and silt loam soil textures. The calibration process was based on the data provided by the capacitive sensors and the continuously and parallelly measured soil moisture content by the thermogravimetric method. It can be stated that the response of the sensors to changes in soil moisture differs from each other, which was also greatly influenced by different soil textures. Therefore, the calibration according to soil texture was required to ensure adequate measurement accuracy. After the calibration, it was found that a polynomial calibration function (R<sup>2</sup> ≥ 0.89) was the most appropriate way for modelling the behaviour of the sensors at different soil textures.</p>
</abstract>

Agriculture faces several challenges to use the available resources in a more environmentally sustainable manner. One of the most significant is to develop sustainable water management. The modern Internet of Things (IoT) techniques with real-time data collection and visualisation can play an important role in monitoring the readily available moisture in the soil. An automated Arduino-based low-cost capacitive soil moisture sensor has been calibrated and developed for data acquisition. A sensor- and soil-specific calibration was performed for the soil moisture sensors (SKU:SEN0193 - DFROBOT, Shanghai, China). A Repeatability and Reproducibility study was conducted by range of mean methods on clay loam, sandy loam and silt loam soil textures. The calibration process was based on the data provided by the capacitive sensors and the continuously and parallelly measured soil moisture content by the thermogravimetric method. It can be stated that the response of the sensors to changes in soil moisture differs from each other, which was also greatly influenced by different soil textures. Therefore, the calibration according to soil texture was required to ensure adequate measurement accuracy. After the calibration, it was found that a polynomial calibration function (R2 ≥ 0.89) was the most appropriate way for modelling the behaviour of the sensors at different soil textures.

Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture

Faculty of Agricultural and Food Sciences

Faculty of Sciences, Department of Mathematics and Informatics

Budapest University of Technology and Economics

Department of Precision Agriculture and Digital Farming

Hungarian University of Agriculture and Life Sciences

Faculty of Science, Department of Environmental and Landscape Geography

Journal of Hydrology and Hydromechanics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Agriculture faces several challenges to use the available resources in a more environmentally sustainable manner. One of the most significant is to develop...

Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture

Pubblicato online: 23 ago 2022

Pagine: 330 - 340

Ricevuto: 03 ago 2021

Accettato: 28 apr 2022

DOI: https://doi.org/10.2478/johh-2022-0014

Parole chiave
IoT, Precision Agriculture, Low-cost capacitive soil moisture sensor, Thermo-gravimetric method, Repeatability and Reproducibility study, Non-linear regression

© 2022 István Mihály Kulmány et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture

Pubblicato online: 23 ago 2022

Pagine: 330 - 340

Ricevuto: 03 ago 2021

Accettato: 28 apr 2022

DOI: https://doi.org/10.2478/johh-2022-0014

Parole chiaveIoT, Precision Agriculture, Low-cost capacitive soil moisture sensor, Thermo-gravimetric method, Repeatability and Reproducibility study, Non-linear regression

© 2022 István Mihály Kulmány et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
IoT, Precision Agriculture, Low-cost capacitive soil moisture sensor, Thermo-gravimetric method, Repeatability and Reproducibility study, Non-linear regression