Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors
Soil volumetric water content (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>V</mi> <mi>W</mi> <mi>C</mi> </mrow> </semantics> </math> </inline-formula>) is a vital parameter to understand...
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2020-01-01
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Soham Adla Neeraj Kumar Rai Sri Harsha Karumanchi Shivam Tripathi Markus Disse Saket Pande |
spellingShingle |
Soham Adla Neeraj Kumar Rai Sri Harsha Karumanchi Shivam Tripathi Markus Disse Saket Pande Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors Sensors volumetric water content soil moisture permittivity capacitive sensor sm100 sensor smec300 sensor resistive sensor off-the-shelf sensor calibration temperature sensitivity, salinity dependence low-cost sensor irrigation management precision agriculture |
author_facet |
Soham Adla Neeraj Kumar Rai Sri Harsha Karumanchi Shivam Tripathi Markus Disse Saket Pande |
author_sort |
Soham Adla |
title |
Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors |
title_short |
Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors |
title_full |
Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors |
title_fullStr |
Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors |
title_full_unstemmed |
Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors |
title_sort |
laboratory calibration and performance evaluation of low-cost capacitive and very low-cost resistive soil moisture sensors |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-01-01 |
description |
Soil volumetric water content (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>V</mi> <mi>W</mi> <mi>C</mi> </mrow> </semantics> </math> </inline-formula>) is a vital parameter to understand several ecohydrological and environmental processes. Its cost-effective measurement can potentially drive various technological tools to promote data-driven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available <inline-formula> <math display="inline"> <semantics> <mrow> <mi>V</mi> <mi>W</mi> <mi>C</mi> </mrow> </semantics> </math> </inline-formula> sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two low-cost capacitive sensors—SMEC300 and SM100—manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very low-cost resistive sensors—the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuru—were tested for performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed in-house and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their precision performance, i.e., the precision performance largely follows sensor costs. The other aspects of sensor performance do not necessarily follow sensor costs. The low-cost capacitive sensors were more accurate than manufacturer specifications, and could match the performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multi-purpose sensing capabilities. The less-expensive SM100 sensor had a better accuracy (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 1.67%, 2.36% and 0.21 respectively) but poorer precision than the SMEC300. However, it was established as a robust, field ready, low-cost sensor due to its more consistent performance in soils (particularly the field soil) and superior performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 3.51%, 5.21% and 0.37 respectively) than YL69 (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very low-cost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low- and very low-cost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems. |
topic |
volumetric water content soil moisture permittivity capacitive sensor sm100 sensor smec300 sensor resistive sensor off-the-shelf sensor calibration temperature sensitivity, salinity dependence low-cost sensor irrigation management precision agriculture |
url |
https://www.mdpi.com/1424-8220/20/2/363 |
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AT sohamadla laboratorycalibrationandperformanceevaluationoflowcostcapacitiveandverylowcostresistivesoilmoisturesensors AT neerajkumarrai laboratorycalibrationandperformanceevaluationoflowcostcapacitiveandverylowcostresistivesoilmoisturesensors AT sriharshakarumanchi laboratorycalibrationandperformanceevaluationoflowcostcapacitiveandverylowcostresistivesoilmoisturesensors AT shivamtripathi laboratorycalibrationandperformanceevaluationoflowcostcapacitiveandverylowcostresistivesoilmoisturesensors AT markusdisse laboratorycalibrationandperformanceevaluationoflowcostcapacitiveandverylowcostresistivesoilmoisturesensors AT saketpande laboratorycalibrationandperformanceevaluationoflowcostcapacitiveandverylowcostresistivesoilmoisturesensors |
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doaj-f79b6e46422d430f83c32c857adba2f52020-11-25T00:35:15ZengMDPI AGSensors1424-82202020-01-0120236310.3390/s20020363s20020363Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture SensorsSoham Adla0Neeraj Kumar Rai1Sri Harsha Karumanchi2Shivam Tripathi3Markus Disse4Saket Pande5Chair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, GermanyKritsnam Technologies Private Limited, Kanpur 208016, IndiaKritsnam Technologies Private Limited, Kanpur 208016, IndiaDepartment of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur 208016, IndiaChair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, GermanyDepartment of Water Management, Delft University of Technology, 2628 CN Delft, The NetherlandsSoil volumetric water content (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>V</mi> <mi>W</mi> <mi>C</mi> </mrow> </semantics> </math> </inline-formula>) is a vital parameter to understand several ecohydrological and environmental processes. Its cost-effective measurement can potentially drive various technological tools to promote data-driven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available <inline-formula> <math display="inline"> <semantics> <mrow> <mi>V</mi> <mi>W</mi> <mi>C</mi> </mrow> </semantics> </math> </inline-formula> sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two low-cost capacitive sensors—SMEC300 and SM100—manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very low-cost resistive sensors—the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuru—were tested for performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed in-house and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their precision performance, i.e., the precision performance largely follows sensor costs. The other aspects of sensor performance do not necessarily follow sensor costs. The low-cost capacitive sensors were more accurate than manufacturer specifications, and could match the performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multi-purpose sensing capabilities. The less-expensive SM100 sensor had a better accuracy (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 1.67%, 2.36% and 0.21 respectively) but poorer precision than the SMEC300. However, it was established as a robust, field ready, low-cost sensor due to its more consistent performance in soils (particularly the field soil) and superior performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 3.51%, 5.21% and 0.37 respectively) than YL69 (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>M</mi> <mi>S</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <mi>A</mi> <mi>E</mi> </mrow> </semantics> </math> </inline-formula> of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very low-cost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low- and very low-cost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems.https://www.mdpi.com/1424-8220/20/2/363volumetric water contentsoil moisturepermittivitycapacitive sensorsm100 sensorsmec300 sensorresistive sensoroff-the-shelf sensorcalibrationtemperature sensitivity, salinity dependencelow-cost sensorirrigation managementprecision agriculture |