Soil Deformation Monitoring System using

Soil Vibration and Moisture Sensors

Yakobus Yulianto Kevin, Erwin Susanto and Husneni Mukhtar

Telkom University, Jl. Telekomunikasi Terusan Buah Batu, Bandung, Indonesia

Keywords: Landslide Monitoring System, Geophone Sensor, Soil Moisture Sensor, Zigbee

Abstract: Landslides are natural disasters that often occur in Indonesia. In 2018 474 landslides in Indonesia resulted in

many fatalities and many damaged buildings. To minimize losses caused by landslides, a tool for monitoring

the soil condition is needed. In this research, sensors of soil vibration and soil moisture were utilized to

develop a monitoring system of soil deformation that was able to perform continuously in real-time. For the

data transfer, the Zigbee module, as wireless data communication, sent the acquired data from both sensors

to Antares as an IoT platform via node-MCU ESP8266. The monitoring simulation of the soil deformation

was carried out on a plant prototype placed indoors by embedding a spring on all four corners or feet of the

plant prototype. Results of this monitoring system were displaying the vibration and moisture data of soil

condition is continuous and real-time. The vibration data from the geophone sensor with 99.97% of sensor

accuracy were sent to the IoT platform and displayed on the monitor. While the moisture sensor (soil moisture

v1.2) with 99.71% of average accuracy. The communication system sending data from the sensor to Antares

produces an average delay of 2.3 seconds.

1 INTRODUCTION

Indonesia is one of the countries prone to natural

disasters globally because it has a geographical

condition that consists mainly of mountains, hills,

valleys, and vast seas. One of the natural disasters that

often occurs in Indonesia is landslides. A landslide is

a geological event that occurs due to rock or soil mass

movement with various types and types, such as

falling rocks or large lumps of soil. According to the

National Disaster Management Agency (BNBP) in

Indonesia, in 2018, 474 landslide incidents in

Indonesia resulted in many fatalities and many

damaged buildings. Landslides usually occur in

mountainous areas, hills, steep slopes, or cliffs. The

cause of landslides is high rainfall, deforested forests,

not dense soil and small vibrations caused by vehicle

traffic around the hillsides. Due to the frequent

occurrence of landslides, we need a monitoring

system of ground movement in a particular area. This

system is that it can monitor the condition of ground

movement continuously in real-time.

Some previous research reports on landslide

warning system can be found, for example, is the

Landslide Warning System on the Railroad Track

(Hartalita, et al., 2018). This study used an

accelerometer sensor ADXL345 with the advantage

of detecting the tilt and converting it to angular

degrees with a sensor accuracy of 96.45%. The

drawback of this sensor is that it cannot follow fast

movements due to its slow response. The other report

uses light sensors, i.e., light-dependent resistor

(LDR), to detect landslide events (Sudibyo,

Herawadi, 2015). The advantage of this sensor is that

it can read ground motion by utilizing light. The

drawback is that the error value obtained from the

measurement is about 5%.

Landslide detection using ultrasonic and infrared

with short message service (SMS) notification was

reported in (Widhiantoro and Purwarupa, 2015). The

advantage of the infrared sensor is that it can detect

the existence of moving objects such as humans and

animals and soil movements. In contrast, the

ultrasonic sensor can be used to detect their

movements. The disadvantage is that if the ground

movement is less than 2 cm, the sensor cannot read

the variations accurately. In this paper, we use a

vibration sensor and humidity sensor to monitor

ground motion. Then the data is processed and

displayed as information on the condition of soil

movement.

Kevin, Y., Susanto, E. and Mukhtar, H.

Soil Deformation Monitoring System using Soil Vibration and Moisture Sensors.

DOI: 10.5220/0010797100003317

In Proceedings of the 2nd International Conference on Science, Technology, and Environment (ICoSTE 2020) - Green Technology and Science to Face a New Century, pages 117-124

ISBN: 978-989-758-545-6

117

2 RESULTS AND DISCUSSION

2.1 Basic Theory

2.1.1 Geophone Sensor

A geophone principle work is the conversion of

ground motion (displacement) into voltage. Zan et al.

deployed a geophone to sense the landslide early

warning system (Zan, et al., 2002). Many types of

vibration signals induced by traffic, train movement

or regular tapping can be sensed by a geophone

(Kunnath, et al., 2010). Geophone has two main

components, namely permanent magnets and wire

windings, shown in Figure 2.1.

Figure 2.1. Main Components of Geophones

Geophone works based on Faraday's law, where

the magnetic flux variations cause the electric current

flow in a coil in varied times. The magnitude of the

stress on a geophone that occurs is directly

proportional to the flux changes concerning time.

Faraday's Law can be stated by the formula below:

𝜀𝑁ΔΦ/Δ𝑡 (1)

where

ε = induced GGL (volts),

N = Number of coil windings

ΔΦ = Change in magnetic flux (weber)

Δt = time-lapse (s)

The negative sign indicates the direction of the

induced electromotive force (emf).

2.1.2 High Pass Filter

High Pass Filter (HPF) is a filter or frequency filter

that can pass high-frequency signals and inhibit or

block low-frequency signals or frequencies under

cut-off frequencies. To determine the value of the

cut-off frequency, it can be calculated using the

formula:

𝑓









(2)

where:

𝑓



= Cut off frequency in units of Hz

π = 3.14

𝑅 = Resistance in Ohms (Ω)

𝐶 = Capacitance in Farad (F)

Figure 2.2. High Pass Filter Circuit

2.1.3 ADS1115 Module

ADS1115 module is a type of ADC with a 16-bit

resolution with a high level of conversion accuracy

compared to the 10-bit ADC. In this ADC, four

channels can convert values for four sensors

simultaneously with bipolar or single differentials.

The received data will be transferred or sent via I2C

serial communication. The series consists of SDA and

SCL. The next Figure 2.3 shows the ADS1115

module.

Figure 2.3. ADS1115 Module

2.1.4 Soil Moisture Sensor

A soil moisture sensor is a sensor that can detect

moisture in the soil. This sensor consists of two parts,

namely the probe and the comparator. In the

comparator part, there is an IC TLC555I that serves

as a voltage comparator. At the same time, the probe

has a function to pass current through the ground and

read the resistance proportional to the value of the

humidity level. Measurement of soil moisture can be

done by the relations of mass of water MA, the mass

of wet soil MTB, the mass of dry soil MTK and soil

moisture KT (Stevanus and Setiadi, 2013):

𝑀𝐴  𝑀𝑇𝐵  𝑀𝑇𝐾 (3)

𝐾𝑇  𝑀𝐴/𝑀𝑇𝐵  100% (4)

Figure 2.4. Soil Moisture Sensor

Many usages of soil moisture sensors can be

found in real applications such as to monitor sports

turf humidity, especially for a golf game, to reveal

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ancient irrigation practices in waterless environment,

etc.

People monitor soil moisture for many beneficial

for environmental researchers and practitioners like

farmers, golf course superintendents, archaeologists,

and regulators (Kumar, et al., 2016).

2.1.5 Zigbee

RF transceiver modules are set in Digi XBee S2C to

provide wireless connectivity using the Zigbee

protocol. The configuration consists of XCTU for the

connection of coordinator and router using AT

commands and MAC addresses. The coverage of the

connection is 60 m indoor and 1200 m outdoor.

Figure 2.5. Zigbee

2.1.6 Arduino Uno

We use Atmega328 Arduino microcontrollers with an

open-source physical computing platform. It contains

20 I/O pins, 14 digital and six analogue pins, a 16

MHz crystal oscillator, a Universal Serial Bus (USB)

connection, a power jack, an ICSP header and a reset

button as shown in Figure 2.6. To embed programs in

Arduino boards, USB-to-serial adapter chips such as

the FTDI FT232 can be employed.

Figure 2.6. Arduino Uno

2.1.7 Node MCU ESP 8266

NodeMCU ESP8266 is an embedded microcontroller

system equipped with Wi-Fi intact. Therefore, it does

not need to use additional Wi-Fi devices. The system

architecture is on the chip (SoC) and has a function

for communicating GPIO by connecting and

transmitting data through the Internet. Figure 2.7

shows the I / O pins of NodeMCU (Shkurti, 2017).

Figure 2.7. NodeMCU ESP 8266

The standard Lua Programming firmware script

was often used to simplify programming, and it

usually needs the existing library in the Arduino IDE

software. This software is open and can be

downloaded and run well in the operating system

(Prayogo and Suryo, 2016).

2.2 System Design

2.2.1 Hardware Design

A block diagram of a deformation monitoring system

of ground motion using a geophone sensor and a soil

moisture sensor is shown in Figure 3.1.

Figure 3.1. Block Diagram

To monitor the ground motion deformation using

a geophone sensor and a soil moisture sensor is to

conduct a two-season trial, namely the dry and rainy

seasons. During the dry season, the signal level

generated from the soil moisture sensor does not

experience any significant changes because the

humidity in the soil tends to be more stable.

Meanwhile, soil conditions tend to be wet during the

rainy season to increase the humidity sensor output

measurement. Unlike the soil moisture sensor, the

level generated by the ground vibration sensor tends

not to be affected by seasonal changes. The geophone

sensor will display a significant change only when

getting vibration.

2.2.2 Software Design

Figure 3.2 shows a flowchart that illustrates the

algorithm of a soil deformation monitoring system

using a geophone sensor and a soil moisture sensor.

Soil Deformation Monitoring System using Soil Vibration and Moisture Sensors

119

The first step that must be done is to initialize the

geophone sensor input and the soil moisture sensor.

Inputs generated by geophone sensors and soil

moisture sensors are analogue signals which the ADC

port will then process on the microcontroller to

convert the analogue voltage to digital voltage. After

that, the Atmega 328 microcontroller will read the

input provided by the sensor. The output signal from

the Atmega 328 Microcontroller will be forwarded to

the transmitter part of the Zigbee module to be sent to

the receiver part of the Zigbee module. The signal

data that the receiver has received will be forwarded

to the Antares using nodeMCU ESP8266 to be

displayed in graphical form.

Figure 3.2. Software Design Flow Chart

2.2.3 Mechanical Design

In Figure 3.4, we can see that mechanical design aims

to provide a general picture of the equipment to be

tested.

Figure 3.3. Mechanical Design

The material used to make the simulation box is

transparent acrylic. The size of the simulation box is

60 cm long, 40 cm wide and 40 cm high. The box was

filled with land that is set close to the actual situation.

Soil moisture sensor is installed in separated 3 sensor

modules while geophone sensors are installed in two

places, namely sensor module 1 and sensor module 3.

Each sensor module is installed with a distance of 5

cm.

2.3 Test and Analysis Results

2.3.1 Testing the Geophone Sensor

Figure 4.1. Linear Regression Chart Using a 0.5 Seconds

Delay

Based on geophone sensor testing in Figure 4.1, 30

data were taken in the testing mechanism at 0.5-

second intervals. The minimum output voltage is 0

volts for less vibration. In contrast, in the under-

vibration state, the maximum voltage of the

multimeter is 2,528 volts, and it equals 2.5 volts on

the serial monitor display. Based on Figure 4.1, the

formula of linear regression can be obtained using an

interval of 0.5:

y=1,0014x+00,086

2.3.2 Moisture Sensor Testing

Table 4.1. Soil Moisture Sensor Testing

Trial

Soil Moisture Value (%) Refe

rence

Value

Sensor 1 Sensor 2 Sensor 3

1 100 99.71 99.69 100

2 100 99.42 99.38 100

3 100 99.71 99.38 100

4 100 99.71 99.07 100

5 100 100 99.38 100

6 100 99.71 99.38 100

7 100 100 99.38 100

8 100 100 99.38 100

9 100 99.71 99.38 100

10 100 100 99.07 100

Avg 100 99.797 99.349 100

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From the experiment results in Table 4.1, the

mean of sensor measurements is 100% (sensor 1),

99.80% (sensor 2) and 99.35% (sensor 3).

2.3.3 Zigbee Testing

- Delay Testing

The following is the experiment result of delay testing

of Zigbee in tabular form.

Table 4.2. Zigbee Test Results

Data

delivery

interval

(seconds)

Average Delay (seconds)

Horizontal Testin

Vertical

Testin

Indoor

3.5 m

Outdoor

10 m

eight o

3,5

Height

of 7 m

1 1,258 3,175 3,985 2,868

2 1,120 1,677 2,839 3,281

3 0,993 1,861 2,014 3,682

4 1,102 1,423 1,577 2,721

5 1,531 1,816 1,918 2,290

10 0,992 1,692 0,517 0,693

15 1,029 1,944 0,514 0,947

20 0,992 2,252 0,503 0,761

25 1 2,268 0,544 1,008

30 0,994 1,754 0,508 1,029

From the data testing results, it can be concluded

that the value at intervals of 1,2,3,4 and 5 seconds

delay is greater than the interval values of 10, 15, 20,

25 and 30 seconds. Moreover, at the 10-second

interval, the resulting data is better than other

intervals.

- Testing Data Loss

Table 4.3. Zigbee Data Loss Testing Results

Data

delivery

interval

(sec)

Average Data Loss (%)

Indoor

3.5 m

Outdoor

10 m

Height

of 3,5 m

Height

of 7 m

1 0 7,196 38,557 0

2 0 1,685 16,176 5,747

3 0 1,667 5,217 38,970

4 0 0 0 10,416

5 0 18,072 40,740 0

10 0 0 0 0

15 0 21,67 0 6,67

20 0 10 0 0

25 0 11,67 0 5

30 0 5 0 15

Based on tests conducted, it can conclude that the

4s interval is suitable because it has the slightest delay

compared to other intervals.

2.3.4 Testing Data Transmission to the

Cloud

- Delay Testing

Table 4.4 Testing Delay from NodeMCU ESP8266 to

Antares

Interval

(seconds)

Average delay

(ms)

1 598

2 329

3 513

4 317

5 407

6 405

7 473

8 475

9 458

10 465

Based on tests conducted, it can conclude that the

4s interval is suitable because it has the slightest delay

compared to other intervals.

- Data Loss Testing

Table 4.5. Testing Data loss from NodeMCU ESP8266 to

Antares

Interval

(

seconds

)

Data Loss

(

)

10 0

Based on Table 4.6, it can be seen that in

conducting data transmission trials, there was no data

loss found in data transmission.

- Overall Sensor Testing

This experiment uses two geophone sensors and three

soil moisture sensors. The node 1 geophone sensor is

installed at the top of the landslide, and the node 3

geophone sensor is installed at the bottom of the

landslide while the humidity sensor is placed in the

ground part of node 1, node 2 and node 3.

Testing scenario:

First, all data were taken randomly to determine the

value of humidity and vibration values during initial

Soil Deformation Monitoring System using Soil Vibration and Moisture Sensors

121

conditions. During 13 minutes, the box simulation is

vibrated twice. After 13 minutes, the researchers

experimented from dry to wet by spraying as much as

1 litre of water to replace rain. After 13 minutes, the

researchers vibrated five times randomly. After

that,

the researchers conducted

an experiment from wet

to dry, namely, installing two light bulbs to dry the

soil. The soil drying process lasts for an entire night.

After that, the researchers conducted another five

random vibrations. The following results are graphs

of the vibration sensor and soil humidity during dry,

dry to wet and wet to dry conditions.

- Dry Conditions

Figure 5.1. Graph of Geophone Voltage Values in Node 1

During Dry Conditions

Figure 5.2. Graph of Geophone Voltage Values in Node 3

during dry conditions

In the two graphs above, the artificial vibrations are

made to 2 vibrations so that the two geophone sensors

detect these vibrations.

Figure 5.3. Capacitive Soil Moisture Sensor V1.2, during

dry conditions

Based on the graph above, when conditions are

dry, the geophone sensor detects two artificial

vibrations. It can conclude that the vibration created

does not affect the soil moisture level.

- Dry to Wet Conditions

Figure 5.4. Graph of Geophone Voltage Value in Node 1

during dry to wet

Figure 5.5. Geophone Voltage Value Charts in Node 3

during dry to wet

When conditions are dry to wet, the number of

artificial vibrations is carried out by five vibrations at

random, and the geophone sensor in node 1 detects a

total of 4 vibrations. In comparison, in node three, the

artificial vibrations detected amounted to 5

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vibrations. The geophone sensor at node three is

installed at the bottom of the landslide so that it is

faster and more sensitive when it receives vibrations.

Figure 5.6. Capacitive Soil Moisture Sensor V1.2 Graph

When Dry to Wet Conditions

Based on the capacitive soil moisture sensor v1.2

chart, the sensor value at nodes 1 and 2 has a good

increase. In contrast, sensor 3 has a rate increase due

to the location of sensor three at the bottom of the soil,

so that it takes a long time for water to seep into the

ground and detect by sensors. In the soil moisture

sensor graph, a dashed line indicates that the

geophone sensor is detecting the vibration at that

time. The test results from dry to wet conclude that

the change in soil moisture does not affect the ground

vibration, of the voltage generated by the ground

vibration sensor is relatively the same.

- Wet to Dry Condition

Figure 5.7. Geophone Voltage Value Charts in Node 1

during wet to dry

Figure 5.8. Geophone Voltage Value Chart in Node 3 when

during wet to dry

In Figure 4.8 and Figure 4.9 both geophones

experience the same increase in voltage. There was an

increase in voltage because, at that time, researchers

conducted artificial vibrations.

Figure 5.9. Capacitive Soil Moisture Sensor V1.2 Graph

during wet to dry

The graph above can conclude that the three

sensors can function well and experience a slight

decrease in per cent humidity. In the graph of

capacitive soil moisture sensor V1.2, there is a dotted

line indicating that the geophone sensor detects the

vibration at that time.

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