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

Title:

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

Creator:

Kulmány, István Mihály, Bede-Fazekas, Ákos, Beslin, Ana, Giczi, Zsolt, Milics, Gábor, Kovács, Barna, Kovács, Márk, Ambrus, Bálint, Bede, László, and Vona, Viktória

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:cb38860d-95d0-45d1-8073-71b2cf690b12
uuid:cb38860d-95d0-45d1-8073-71b2cf690b12
doi:10.2478/johh-2022-0014

Subject:

IoT, precision agriculture, low-cost capacitive soil moisture sensor, thermo-gravimetric method, repeatability and reproducibility study, and non-linear regression

Type:

model:article and TEXT

Format:

počítač and online zdroj

Description:

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 thermo-gravimetric 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.

Language:

Slovak

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

330-340

Source:

Journal of hydrology and hydromechanics | 2022 Volume:70 | Number:3

Harvested from:

CDK

Metadata only:

false