Comparative Analysis and Calibration of Low Cost Resistive and Capacitive Soil Moisture Sensor Sourodip Chowdhury Shaunak Senand S Janardhanan

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Comparative Analysis and Calibration of Low Cost Resistive and

Capacitive Soil Moisture Sensor

Sourodip Chowdhury∗, Shaunak Sen∗and S Janardhanan∗

Abstract— Soil moisture is an essential parameter in agri-

culture. It determines several environmental and agricultural

activities such as climate change, drought prediction, irrigation,

etc. Smart irrigation management requires continuous soil

moisture monitoring to reduce unnecessary water usage. In

recent times, the use of low-cost sensors is becoming popular

among farmers for soil moisture monitoring. In this paper, a

comparison of low-cost resistive and capacitive soil moisture

sensors is demonstrated in two ways. One way is the calibration

of the sensors in gravimetric and volumetric water content,

and the other is the sensors’ response analysis when different

quantities of water are added to the same amount of soil. The

analysis shown in this work is essential before choosing cost-

effective sensors for any soil moisture monitoring platform.

I. INTRODUCTION

Soil moisture (SM) is an essential agricultural parame-

ter used to estimate various environmental and agricultural

activities such as climate change, drought prediction, and

irrigation scheduling, especially for estimating water stress

in agrarian land [1], [2]. Thus it has become the center of

attraction among other agricultural research areas. Adequate

prediction and estimation of different environmental and

climatic variables require in-situ measurement to be reliable

and precise [3].

SM measurement can be carried out in two ways, direct

measurement and indirect measurement. The gravimetric

method is the direct and natural way to measure SM.

However, it is very labor-intensive and time-consuming,

although it accurately gives ground truth data of soil moisture

content [4], [5]. All other SM measurement technique comes

under the indirect measurement method, indirect because

they use the change in the internal property of the sensory

system as a proxy for soil water content (SWC). Apart

from the gravimetric method, ground contact type sensors

can measure direct information on soil moisture content

(SMC). In the ground contact type sensor category, time-

domain reﬂectometry, time-domain transmission, frequency

domain reﬂectometry, neutron probe, electrical resistance,

electromagnetic sensors, and tensiometers are widely used

[5]–[9]. However, due to the setup cost and bulkiness, these

methods are less preferred for soil moisture monitoring [4],

[5], [10], [11].

SM monitoring using the Internet of Things (IoT) based

intelligent sensor system is prominently used in the recent

era [12]. However, before developing an IoT-based SM

monitoring, we need to focus on the sensor performance.

Predominantly capacitive and resistive sensors are used for

∗Department of Electrical Engineering, Indian Institute of Technology,

Delhi-110016.

IoT-based SM monitoring system [13], [14] as the sensors

are less costlier and have easy setup requirements than

other ground contact sensors. The ground contact sensors

are an indirect method of SM measurement, so they need

calibration. The resistive sensor works based on the change

in conductivity, and the capacitive sensor works based on

the change in the dielectric constant. They provide output in

terms of voltage. So they need to be calibrated in terms of the

SWC [13]–[15] before integrating into a moisture monitoring

platform.

Calibration of the low-cost capacitive sensor has been

performed in [1], [13] and validation with the gravimetric

method shown for an automated soil moisture monitoring

platform. Various investigation on the calibration method,

calibration performance, and veriﬁcation has been conducted

in [14], [16], [17]. A comparison of low-cost resistive and

capacitive sensors was investigated in [14], [18] and the

calibration performance is compared using R2value, RMSE,

MAPE, and RAE.

In work, we aim to investigate the performance of resistive

and capacitive sensors based on different features to compare

their applicability and reliability. Initially, we compare the

calibration results based on the R2value, RMSE, and the

variance on repetition. Later they are compared based on the

response for a different amount of water added to the same

soil.

II. MATERIALS AND METHODS

A. Soil Moisture Sensor

Soil moisture is the interpretation of liquid or water

content in the soil. There are many methods used for soil

moisture measurement. Direct soil moisture measurement

is done using the gravimetric method, but due to the rig-

orousness and labor intensiveness, it is not preferred for

monitoring soil moisture. Indirect methods are based on the

measurement of the change in physical properties of the

soil as a proxy for soil moisture. Sensors generally work on

the indirect principles, where the difference in the physical

quantity reﬂects an electrical quantity.

The capacitive soil moisture sensor works on the principle

of change in dielectric constant due to change in SWC. The

capacitance-based sensing probe comes within a module that

includes 555 timer IC to count the resonant frequency as

an indirect measure of SWC. The resistive soil moisture

sensor operates on the idea of change in resistance when

current conductivity between the probes changes in response

to a change in SWC. The change in the moisture content

is measured using the LM393 comparator circuit that comes

arXiv:2210.03019v1 [cs.NI] 6 Oct 2022

with the sensor probes. The raw output from both the sensors

is in terms of voltage, digitized in the range 1 to 1024. The

raw data or the output voltage is inversely proportional to

the SWC.

Voltage Output =Raw Sensor Output

1024

×3.3V(1)

B. Data Acquisition System

A NodeMCU and a power supply unit are included in

the data acquisition system. NodeMCU is an open-source

ﬁrmware and development board with an integrated ESP-

8266 WiFi module that allows the board to connect to the

internet and send sensor data to the cloud.

C. Cloud Platform

Thingspeak [13] is an open-source IoT analytics platform

by Mathworks. It is generally used for storing, visualizing,

and monitoring sensor data. Thingspeak provides different

channels and corresponding read and writes API keys, using

which data are sent to the platform. Data can be read directly

from the Thingspeak medium using the read API key through

MATLAB online for further analysis.

D. Soil Water Content (SWC)

SWC is the measure of soil moisture, it is interpreted in

two ways, gravimetric water content (GWC, denoted as θg)

and volumetric water content (VWC, denoted as θv) [15],

[19]. GWC is measured as the weighted amount of water

present per weighted amount of soil. VWC is measured as the

volume of water present per volume of soil. The interrelation

between GWC and VWC is given below,

θg=Mw

=Mwet −Md

.(2)

Mw,Ms,Mwet and Mdare the mass of the water present in

the soil, mass of the soil, mass of the wet soil and mass of

the dry soil respectively.

θv=Vw

ρw

ρs

,(3)

θv=Mw

·ρs

ρw

,(4)

θv=θg·ρs.(5)

ρwis the density of water, assumed to be 1 gm/cm3. Thus the

ﬁnal equation 5 shows a relation between GWC and VWC,

where ρsis the bulk density of the soil. The bulk density of

soil is calculated as the ratio of the weight of dry soil to the

volume of the soil, given in Equation 6 [19].

ρs=ρbulk =Weight of dry soil

Volume of soil .(6)

The dry weight of soil is calculated using the GWC from

the equation 2,

Dry soil weight =Weight of the soil (wet)

1+GWC .(7)

E. Calibration Method

The experiment has been performed in Control Laboratory

in the Department of Electrical Engineering at IIT Delhi. The

calibration is performed using clay type soil available in the

campus.

Fig. 1. Sensor Data collection from different soil sample

The experimental requirements were six containers, one

oven for drying purpose, sensor arrangements, zipped lock

plastic bags, weighing machine with 10mg resolution. The

calibration experiment ﬂow is given in Fig. 2. The experi-

mental outcome produce the GWC value, the VWC is then

calculated using the obtained GWC and bulk density of each

soil volume.

Fig. 2. Experimental Design

F. Sensor Response Study

The response study of the resistive and capacitive soil

moisture sensors has been performed for different quantities

of water addition to the same quantity of soil. This exper-

iment is planned in such a way that the sensor response

is independent of any other environmental parameters, such

as ambient temperature variation, humidity to compare the

results. The experiment has been performed in laboratory

and the experiment data is sent to Thingspeak, later they are

collected and processed for drawing insights.

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ComparativeAnalysisandCalibrationofLowCostResistiveandCapacitiveSoilMoistureSensorSourodipChowdhury,ShaunakSenandSJanardhananAbstractSoilmoistureisanessentialparameterinagri-culture.Itdeterminesseveralenvironmentalandagriculturalactivitiessuchasclimatechange,droughtprediction,irrigation,etc.Smar...

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Comparative Analysis and Calibration of Low Cost Resistive and Capacitive Soil Moisture Sensor Sourodip Chowdhury Shaunak Senand S Janardhanan

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