Framework for Internet of Things in Remote Soil Monitoring

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2020 23rd International Conference on Computer and Information Technology (ICCIT), 19-21 December, 2020.
978-0-7381-2333-2/20/$31.00 ©2020 IEEE
Framework for Internet of Things in Remote Soil
Monitoring
Chinmay Bepery
Patuakhali Science and Technology
University
Patuakhali, Bangladesh
Email: chinmay.cse@pstu.ac.bd
Md. Mafrul Alam
Ministry of Power, Energy and Mineral
Resources
Dhaka, Bangladesh
Email: jony.pstu@gmail.com
Md. Shafak Shahriar Sozol
Patuakhali Science and Technology
University
Patuakhali, Bangladesh
Email: shahriarsajal05405@gmail.com
Md. Mahbubur Rahman
Patuakhali Science and Technology
University
Patuakhali, Bangladesh
Email: mahabub.cse.pstu@gmail.com
Md. Naimur Rahman
Patuakhali Science and Technology
University
Patuakhali, Bangladesh
Email: naimur.cse4th@pstu.ac.bd
Abstract—To meet the rising food demands, the technological
implication in farming is emerging. Proper soil monitoring
plays a vital role in agricultural production. Internet of Things
(IoT) based soil monitoring system is used to maximize the
yield of crops or plants by observing soil parameters and
providing the necessary information to the farmers remotely.
In general, the diagnosis of soil properties of the field is
executed through manual laboratory testing. But this can be
accomplished in real-time through IoT, where some
agricultural soil sensors are engaged for remote sensing.
Optimal utilization of resources is crucial in real-time sensors’
data monitoring. After analyzing the acquired data, one can
get useful inference about the recommendation of crops,
fertilizer, and so on in the field. This research deals with
several remote soil monitoring systems based upon IoT
protocols developed by different researchers to increase crop
yields and also provide an overview of sensors, technologies,
benefits, challenges, and future aspects of systems. This
research also proposes a general framework for IoT based soil
monitoring system by using existing technologies.
Keywords—Internet of Things, Remote Soil Monitoring,
Raspberry Pi, Cloud.
I. INTRODUCTION
The agricultural sector has recently changed by applying
the Internet of Things (IoT) to empower farmers with the
vast difficulties they face in everyday life. Recent
developments in IoT applications attempt to solve the issues
by expanding production parameters like quality, amount,
supportability, and cost-viability in the agricultural sectors.
IoT influences farmers to monitor crop growth, soil moisture,
soil temperature, and humidity, soil nutrients, etc. by using
sensors to manage and control irrigation equipment remotely
and make decisions easily. Farmers can effectively take
proper and precautionary steps through the apps on their
smartphones and web pages. IoT connected sensors inform
the farmer of the current soil and crop status in their field. A
gigantic network of devices communicates with one another
in the automated mode requiring absolutely no human
interaction. It would also help him to monitor and adjust the
necessary soil parameters to increase crop production. This
research gives the information related to IoT's fundamental
idea in soil characteristics monitoring and past work utilized
in the field of farming utilizing IoT and remote sensor
arrange for observing and controlling the soil parameters.
The related work is given in section II. A comparative
discussion of the considered research work is shown in
section III. The proposed framework is given in section IV,
and finally, the conclusion is given in section V.
II. RELATED WORKS
An IoT based soil monitoring system to measure soil pH,
soil temperature and moisture by existing sensors developed
on the STM32 Nucleao platform has been described in [1].
Bluetooth is used as a communication module. A system can
monitor and measure soil moisture of black and red soil
using IoT cloud computing and the android system [2]. An
IoT system that monitored agriculture farms continuously to
measure the soil moisture [3]. A wireless sensor network
technology provides soil and crop monitoring using soil
moisture, pH, temperature, humidity, and light-dependent
resistive sensors [4]. In [5], the system extracted the soil's
behavioral nature by using sensors to find out the right crop
for the field has been rendered. Proper irrigation
management in plants using a soil moisture sensor [6]. An
IoT based real-time monitoring system has been discussed
in [7] where Thingspeak cloud server is used. In [8], a
wireless sensor network(WSN) based soil moisture
monitoring system is developed. Exponential Weighted
Moving Average (EWMA) is applied here to overcome the
energy depletion due to communication among sensor nodes
in WSN. Intelligent data analysis performed in [9]. In [10],
the Bluetooth based system can determine the quality and
quantity of the nutrient of soil to recognize which type of
soil is good to grow the crop. In [11], a WSN based IoT
system can monitor soil nutrients by NPK sensors where
cloud and mobile application is integrated. A remote
monitoring system measures soil pH to suggest pesticides
[12]. In [13], automatic irrigation and measurement of soil
nutrients, Nitrogen(N), Phosphorus(P), and Potassium(K)
system is developed to lessen the required quantity of the
fertilizers. In [14], the system integrates the Arduino and
GSM network to monitor soil parameters. In [15], the
system integrates Raspberry Pi and mobile application. A
remote monitoring system is proposed in [16] where an
infrared sensor is used to detect diseases in plants. In [17],
remotely monitoring irrigation system is proposed smoke
and temperature sensors are included to detect danger. The
resistive moisture sensor is less stable and more sensitive
than the capacitive moisture sensor is shown in [18]. In [19],
the proposed system can find suitable crops for the soil and
suggest the required amount of fertilizer for different crops.
The proposed system uses a machine learning approach for
smart irrigation [20]. A solar energy-based IoT system is
proposed in [21]. An IoT based soil health monitoring
technique is proposed in [22] which recommend optimal

resource utilization. In [23], an IoT-based advanced farming
system integrated with image processing is proposed to
select the soil's best crop. A real-time agricultural
monitoring system is developed in [24] where RF433MHz
radio communication module and an ethernet shield are
integrated. An automated smart irrigation and monitoring
system is proposed in [25] where Arduino Uno and
Thingspeak cloud server are integrated. An IoT based plant
monitoring system is developed [26] where machine
learning is used. In [27], the authors described an irrigation
solution by analyzing soil moisture temperature and
humidity values. An IoT-based system manages the excess
water log in the farmland and analyzes the macro-nutrients
in soil [28]. In [29], the authors described an IoT based soil
health monitoring and recommendation system, is validated
using t-tests and authorized laboratory. An IoT based smart
water quality measurement system is proposed in [30].
III. DISCUSSIONS
This review paper has collected articles that have
concentrated on mainly IoT-based soil analysis from 2016 to
2020.
Table 1. List of string for searching
Sl String
1 “IoT”
2 “Internet of things”
3 “Remote monitoring soil characteristics through IoT”
4 “Soil monitoring through IoT”
5 “Wireless sensor network based soil monitoring”
6 “Field monitoring through IoT”
7 “IoT based crop field monitoring”
8 “Monitoring soil quality parameters through IoT”
9 “Soil nutrients detection system based on IoT”
10 “Real-time embedded based soil analyzer”
11 “Soil monitoring using IoT and Machine learning”
12 “Data analysis of IoT based soil sensor data”
The obtained insights are shown and discussed through
tables, figures, charts, flow diagrams, tree diagrams, etc.
Table 1, represents the set of search string which are used for
searching resources.
Table 2. Sources used for the searching publication
Information
Source
Type URL Content
collection
IEEE Xplore Digital
Library
https://ieeexplore.ie
ee.org/Xplore/
Conferenc
es,
journals,
Science
Direct
Digital
Library
https://www.scienc
edirect.com/
Elsevier Digital
Library
https://www.elsevi
er.com
Springer link Digital https://link.springer
Information
Source
Type URL Content
collection
Library .com/ databases,
proceeding
s, and
magazines.
Cite seer Digital
Library
https://citeseerx.ist.
psu.edu/index
Google
Scholar
Search
Engine
https://scholar.goog
le.com/
Microsoft
Academic
Search
Engine
https://academic.mi
crosoft.com/home
Table 2 represents the sources. We have used four steps to
select articles, i.e., identification, selection, eligibility, and
inclusion. Thus, the 29 publications effectively extracted.
The sensor parameters usability of the selected articles is
shown in figure 1. This study shows that soil moisture
sensors (30%) and soil pH sensors (14%) are used most in
IoT-based soil monitoring.
Figure 1. Used sensors in selected publications
The used technologies of the selected papers are shown in
figure 2. It indicates that Mobile technology (26%),
Raspberry Pi (20%), Wi-Fi (15%) are used in recent IoT
based soil analysis.
Figure 2. Used technologies in selected publications
Table 3 shows the used wireless technologies. We also get
an insight that the machine learning mechanism gradually
increases in this field. Twenty-seven percent (27%) of the
total considered articles integrate machine-learning
mechanisms. Table 4 shows the essence of considered
articles.
Table 3. Wireless technologies used in considered IoT based soil-monitoring systems
Technology Standard Discovery year Operating frequency Data rates Range
Bluetooth IEEE 802.15.1 1999 2400-2483.5 MHz 1-24 Mbps 10-100 m
Wi-Fi IEEE 802.11 1997 2.4,3.6,5,60 GHz 1 Mbps-6.75 Gbps 20-100 m
Zigbee IEEE 802.15.4 1998 2400-2483.5MHz 250 Kbps 10-100 m
RFID Wireless 1983 13.56 MHz 423 kbps 100m
GSM Many standards 1997 800-900 MHz 9.6 Kbps 35 Km
6LoWPAN Wireless 2006 915 MHz 250 Kbps 30 m

Table 4.
Analytical
summary of
29 peer
-
reviewed
IoT based
soil monitoring
publication
s from
2016
-
2020
Ref. Measuring Data Devices Cloud Strength/
Benefits
Weakness Future Scope
[1]
•
Soil temperature
• Soil pH
• Soil moisture
•
Bluetooth
• Mobile
•
STM32
NUCLEO
platform
•
Real-time
• Low cost and efficient
system
•
Sufficient
sensors
•
High power
consumption
•
Sensor accuracy and
power efficiency
• 6LoWPAN technology
[2]
•
Soil moisture
•
Wi-Fi
• Mobile
•
AT&Ts’
M2X Cloud
•
Measures red and
black soil moisture
•
Poor and
complex setup ------
[3]
•
Soil moisture
•
Wi-Fi
•
Losant
•
Low-cost system
• Synchronized with
losant platform
•
Required good
technical
knowledge
------
[4]
•
Soil moisture
• Temperature,
light and
humidity
• Water level
•
Mobile
•
AGRO-
TECH
•
Efficient power
management
• Reduce
communication cost
•
Overhead
sprinklers
•
Can be recorded and
monitored different
aspects by using a drone
and other technology
[5]
•
Soil pH
• Temperature and
humidity
• Plant image
•
Mobile
• Raspberry Pi ------
•
Increase production
and overall yield
• Reduce time and cost
•
High power
utilization ------
[6]
•
Soil moisture
•
Wi-Fi ------
•
Economical and low
maintenance cost
•
Technical
constraints
•
Neural network to
predict seasonal change
[7]
•
Soil moisture
• Light intensity
• Humidity
• Soil temperature
•
Wi-Fi
• Mobile
•
Thingspeak
•
Smart irrigation
control
•
System
scalability and
manageability
is low
------
[8]
•
Soil moisture
•
Zigbee
• Raspberry Pi 3
•
Dropbox
•
Low energy
consumption
•
Relatively
expensive
•
Can be added more than
one sensor module
[9]
•
Soil moisture
• Soil nutrients
• Water flow rate
•
Arduino
ethernet shield
• Zigbee
•
Ubidots
•
Efficient water
management
•
Poor risk and
power
management
•
Offline analysis of NPK
remote data
[10]
•
Electrical
conductivity
• Soil pH
• Color texture
•
Bluetooth
• Mobile ------
•
Directly send the farm
statistics to the server
and get a suggestion
for better fertilization
•
No economic
feasibility
•
Complicated
data
•
A very low-cost portable
device & mobile
application can be
developed
[11]
•
Soil fertility
information
(NPK)
•
Zigbee
• Mobile
•
IBMBLUE
MIX cloud
•
Prescribe quantity of
fertilizers to grow the
more economical crop
•
Can’t provide
exact NPK
prescription
•
Other sensors (moisture,
pH etc.) and mobile
application can be joined
[12]
•
Soil pH
• Soil temperature
• Soil moisture
•
GSM
• Mobile ------
•
Measure soil pH rate
with very minimal
cost
•
No feasible
experiment
•
More effective sensors
will be interfaced
[13]
•
Soil nutrients
(NPK)
• Soil temperature
• Soil moisture
• Color texture
• ARM7
LPC2138 ------
•
Sensing data is
transferred to the user
through email
• Lack of water
management
•
No good IoT
module is used
for transferring
the sensing
data
•
More soil parameters
will be added for
monitoring and update
the user through a mobile
app.
[14]
•
Soil moisture
• Soil temperature
• Soil pH
•
GSM Module
• Mobile ------
•
Automated and
operated over a wide
area by consuming
less power
•
Security issues
•
Protection of
sensors is not
good
•
Minerals of the soil
• Sensors protection can be
provided during bad
weather
[15]
•
Soil pH,
moisture
• Temperature and
humidity
•
Raspberry Pi
•
Apache
server
•
Performance is quite
reliable and accurate
•
Lack of
resource
management
------

Table 4.
Analytical
summary of
29 peer
-
reviewed
IoT based
soil monitoring
publication
s from
2016
-
2020
Ref. Measuring Data Devices Cloud Strength/
Benefits
Weakness Future Scope
[16]
•
Soil pH,
moisture
• Temperature and
humidity
• Infrared heat
image
•
Raspberry pi
•
Thi
ngspeak
•
Give efficient
productivity of crops
• Broader coverage
•
Lack of
nutrition
management
•
Lack of useful
inference
•
The electrochemical
sensor can be used which
determine the pH range
of each nutrient
separately
[17]
•
Soil moisture
• Smoke detection
• Soil temperature
•
NRF24L01
• Raspberry Pi
•
Firebase
•
Efficient watering
system & An
adequate distance
control mechanism
•
Can’t handle
the abnormal
situation
•
To find the affected
crops and care for the
crops by taking
necessary steps
[18]
•
Soil moisture
capacitive and
resistive value
• Temperature and
humidity
•
Wi-Fi
•
Thingspeak
•
Low cost for devices
• Effective water
management
•
Complex
analysis
------
[19]
•
Soil pH
• Soil temperature
• Humidity and
temperature
• Soil moisture
•
Zigbee
------
•
Water conservation is
maintained
• Maintaining the
proper temperature
inside the greenhouse
•
Limited to
greenhouse
•
Better cloud storage, data
analysis, and
visualizations of data can
be done in future
[20]
•
Soil moisture
•
Raspberry Pi
• Mobile
------
•
Can control the motor
automatically for
irrigation on plants
•
Hard to water
equality due to
unequal
rainwater
•
The Machine learning
approach will be
improved
[21]
•
Soil salinity
• Soil moisture
• Temperature and
humidity
•
Raspberry Pi
• Mobile
•
Apache
server
•
Efficient power
management through
the solar panel
• Give a good solution
against saline water
intrusion issue
•
Lack of user-
friendly data
representation
•
Lack of useful
inference
•
Can be developed a plant
diseases detection system
& FPGA controlled
shared smart antenna
[22]
•
Soil moisture
• Nitrogen
through NIR
•
TICC32OO
microcontrolle
r
------
•
Low cost and energy-
efficient system
•
Improper
maintenance
------
[23]
•
Plant image
• Soil pH
• Soil moisture
• Soil nutrients
•
Raspberry Pi
------
•
Can detect soil pH,
moisture level, and
nutrients of the soil
effectively
•
Lack of proper
fertilizers
recommendatio
n
•
Many other devices and
sensors can be added
depending upon the need
[24]
•
Soil moisture
• Soil pH
•
Radio module
• Arduino
ethernet shield
------
•
Real-time soil pH and
moisture monitoring
from any anywhere
•
Difficult to
install extra
devices
------
[25]
•
Temperature and
humidity
• Soil moisture
• Light intensity
•
Wi-Fi
•
Thingspeak
•
Provide energy
conservation,
efficiency, and time-
saving
•
Incapable of
unpredictable
weather -------
[26]
•
Soil moisture
• Soil temperature
• Temperature and
humidity
• Light intensity
•
Wi-Fi
•
Thingspeak
•
Provide great scope in
the artificial farming
field
• Recommend suitable
crop on targeted land
•
Intensification
management in
machine
learning
techniques
------
[27]
•
Soil moisture
• Temperature and
humidity
•
Raspberry Pi
•
Wi-Fi IoT
Logs
server
•
Efficient water
management system
•
Incapable of
unpredictable
weather
------
[28]
•
Soil moisture
• Water level
• Soil pH
•
Zigbee
• Mobile
•
Thingspeak
•
Provide suggestions
on fertilizers based
upon the pH value
•
A Large
number of
measurements
------

Table 4.
Analytical
summary of
29 peer
-
reviewed
IoT based
soil monitoring
publication
s from
2016
-
2020
Ref. Measuring Data Devices Cloud Strength/
Benefits
Weakness Future Scope
•
Temperature and
humidity
•
Good water
management system.
•
Expensive
[29]
•
Soil moisture
• Soil pH
• Temperature and
humidity
•
Bluetooth
• Mobile ------
•
Easy to install,
control, maintain, and
more user friendly for
farmers
•
Can’t predict
the time of
watering
•
The electrical
conductivity of soil will
be measured in future
IV. PROPOSED GENERALIZED IOT BASED SOIL
MONITORING SYSTEM
Proper and efficient cultivation depends on various soil
parameters. Various soil sensors like pH sensor, moisture
sensor, nutrients sensor (NPK sensor), temperature and
humidity sensor, salinity sensor, etc. can be used for this
measurement. In this proposed system, the soil moisture, soil
temperature, temperature and humidity sensor can be
integrated for an effective irrigation system.
Figure 3. Proposed generalized IoT based soil monitoring system
The salinity sensor can be used to detect saltwater intrusion.
Soil pH sensor indicates whether the soil contains acidic or
alkaline. Soil salinity, soil pH sensor, soil nutrients sensors
can generally be used for fertilizer recommendation system.
The camera sensor can be used for providing crops or plants
image. Through image processing, crop diseases can be
diagnosed, and farmers can then take necessary steps as per
requirement. Sensed data of these sensors go to the anchor
device. The proposed framework is given in figure 3.
According to the requirement, the anchor device process the
sensed data and transfer to the cloud through wireless
communication (Bluetooth/ Wi-Fi/ Zigbee/ Radio/GSM etc.,)
module. Within the cloud, machine learning or automatic data
analysis can be performed on these IoT data and extracted
useful information for farmers to make the appropriate
decision. A web-based platform and a mobile application can
be developed where stakeholders are interfaced according to
their responsibility. The authorized users can observe the data
from anywhere. IoT based remote control agricultural
equipment (cultivation, irrigation) can be attached to this
system. The power system for operating all the electric
components integrating with this proposed system is from the
battery and energized by renewable solar energy. This
proposed generalized framework can be used to develop a
scalable, power reliable, web-based user-friendly system. The
proposed framework will provide the following benefits:
1. Scalable system for sensors integration and suitable
crops can be prescribed.
2. Effective fertilizer recommendation and water
management can be accomplished.
3. The solar power system can be used as an alternative
power source.
This proposed sensor-based integrated framework would
measure all kinds of soil parameters in a real-time manner. It
can be followed for developing IoT based soil monitoring
system.
V. CONCLUSION
This paper provided a comprehensive study of recent IoT
based soil characteristics monitoring system. This article tries
to find out the current state of IoT (sensors, communication
technology, attached hardware, cloud platforms, user
interface, power system, challenges and benefits) in remote
soil monitoring. A generalized framework for IoT based soil
monitoring system is proposed where major soil features
extraction sensors are integrated. The proposed framework
can be used to develop an IoT based integrated agriculture
management system. This review would help new researchers
to find new ways and solutions in soil monitoring and make
the process more effective and efficient.

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