Application of the internet of things technology (IoT) in designing an automatic water quality monitoring system for aquaculture ponds
ISSN 2588-1299
VJAS 2020; 3(2): 624-635
Vietnam Journal
of Agricultural
Sciences
Application of the Internet of Things
Technology (Iot) in Designing an Automatic
Water Quality Monitoring System for
Aquaculture Ponds
Nguyen Quang Huy1, Vu Thi Thu Giang2, Le Vu Quan1 & Ho The
Vo Cuong1
1Faculty of Engineering, Vietnam National University of Agriculture, Hanoi 131000,
Vietnam
2Faculty of Information Technology, Vietnam National University of Agriculture, Hanoi
131000, Vietnam
Abstract
The current paper aims to apply the Internet of Things technology
(IoT) in designing an automatic system for measuring and monitoring
important parameters of aquaculture ponds such as temperature, pH,
and dissolved oxygen (DO). The system includes the Arduino Nano
main microcontroller (the device that transmits and pushes data to the
Raspberry Pi 3 Web server), the DS18B20 temperature sensor
module, the pH sensor module V1.1, and the DO Sensor SKU
SEN0237. The system is capable of continuously measuring the
above parameters of aquaculture ponds. The measurement results are
stored and transmitted wirelessly to smart devices such as computers
and mobile phones. Farmers can continuously monitor water quality
parameters of aquaculture ponds (pH, DO, temperature) through
these smart devices. In addition, a warning message will be sent to
the farmer's phone when the DO index of the aquaculture pond falls
below the prescribed level. The results of the test evaluation also
show the high accuracy of the system when compared with the
sample measuring device. All relative errors are satisfied less than
the limit value of 5%.
Keywords
IoT, Arduino Nano Micro, Raspberry, sensor, pond monitoring
Introduction
Vietnam is a country with a dense system of rivers and long
seaways, which is very convenient for developing fishing and
aquaculture activities. According to data from the Vietnam
Association of Seafood Exporters and Producers (2020), Vietnam's
seafood production has maintained continuous growth over the past
17 years with an average increase of 9.07% per year. With the
Received: April 12, 2020
Accepted: July 31, 2020
Correspondence to
624
Vietnam Journal of Agricultural Sciences
Nguyen Quang Huy et al. (2020)
Vietnamese government’s policy of
promoting the development of the aquaculture,
aquaculture activities have made strong
development steps, the output from aquaculture
activities has continuously increased over the
years with an average of 12.77% increase per
year, making a significant contribution to the
growth of the country's total fishery output.
According to a report by the General Department
of Fisheries (2020), the value of fishery
production in 2018 reached about VND
228,139.8 billion, an increase of 7.7% as
compared to 2017. The total output reached
about 7.74 million tons, an increase of 7.2%, of
which fishing output reached 3.59 million tons,
up 6.0%, aquaculture reached 4.15 million tons,
up 8.3%, respectively.
exceeds the threshold limits, aquatic animals will
be affected. For example, low DO in the water
will lead to difficulty in breathing for aquatic
organisms which may threaten their lives.
Therefore, it is imperative to control all water
quality indicators and have timely treatments to
ensure they are within the threshold limits.
Among the above water quality indicators,
there are some fast-changing indicators
(continuously changing during the day) such as
DO, pond temperature, and pH. These indicators
need to be tracked and monitored all the time of
the day. The remaining indicators, due to the low
speed of change, can be monitored by test kits
(KIT) or hand-held meters to reduce the
investment cost for the monitoring system. Table
1 presents the limit of DO thresholds for some
aquatic animals.
Water quality in aquaculture ponds plays a
crucial role in the growth and development of
aquatic animals. Indicators that directly influence
water quality in aquaculture ponds are DO
concentration, temperature, pH, NH3, Nitrite,
H2S, alkalinity, salinity, mineral concentration,
nitrate concentration, phosphorus concentration,
bacterial density, and algae density, etc. All of
these indicators must be within the threshold
limits. As long as one of the above indicators
Recently, in Vietnam, the indicators of water
quality of aquaculture ponds are mainly
measured by hand-held meters as shown in
Figure 1. These methods are not very effective
since they must use manpower and can only be
conducted manually a few times a day.
Therefore, the water quality parameters of
the pond are not monitored continuously and
may have brought inaccurate information.
Table 1. Threshold limits of DO of some aquatic animals (Vietnam Fisheries Society, 2018)
Critical limit of dissolved oxygen
Aquatic animal
(mg L-1)
Dead zone (mg L-1)
Coldwater fish
Warmwater fish
Shrimp
5.0 - 6.0
4.0 - 5.0
3.0 - 4.0
2.5 - 3.5
1.0 - 2.0
0.5 - 1.0
Figure 1. Some types of equipment for measuring DO in aquaculture ponds (Baonghean, 2020)
625
Application of the Internet of Things technology in designing an automatic water quality monitoring system for aquaculture ponds
Currently, the strong development of science
and technology, especially the Internet of Things
(IoT) and computer science, has led to the
introduction of wireless measuring devices and
sensor networks (Wireless sensor networks). IoT
is a highly promising technology that is offering
many innovative solutions to modernize the
agriculture sector. Throughout the world, IoT
and wireless technologies have been studied and
applied in many different fields of agriculture
such as farms and growers, fisheries, animal
husbandry, and agribusiness supply chains.
Existing research in this field has usually focused
on measurement and monitoring of production
environment parameters (Akhmetov & Aitimov,
2015; Ran, 2014), precision agriculture (Lin,
2015), improving product quality (Athanasios &
Charalampos, 2010), and building a data
management system forensuring food safety
(Liu, 2015).
(smartphones) or computers. Moreover, the
system is also able to send warning messages to
farmers immediately when the water quality
indicators of the ponds are below the threshold
limits.
Materials and Methods
Overall structure of the system
The ovarall structure of the automatic
measurement and monitoring system of the
parameters in aquaculture ponds is illustrated in
Figure 2.
The indicators of the aquaculture ponds such
as temperature, pH, and DO are measured by
sensors and then converted into voltage signals
that are sent to the Arduino Nano central
microcontroller. The microcontroller processes
signals according to the installation algorithm,
the data is then transferred to the Raspberry Pi3
block where the data is processed and pushed to
the Web server. Users can use computers or
smartphones with a network connection to track
and monitor the parameters of aquaculture
ponds, such as temperature, pH, and DO
concentration, through the ThingSpeak interface.
Besides, when the DO level in the pond falls
below the threshold limit, the system will send a
warning message to the farmer's phone via a SIM
900 A module and turn on the aerator to timely
supply additional DO to the pond.
In Vietnam, the application of IoT
technology in agricultural production has been
initially researched and sporadically conducted.
Binh & Tri (2016) presented the simulation of
measuring environment temperature in ponds
using Matlab programming language. In their
work, they build a virtual pond combining
DS18B20 temperature sensor with Arduino
microcontroller circuit and MATLAB software,
and then create a tool to collect, store, and
retrieve temperature data in a 3D environment of
the virtual pond. In the study by Duy et al.
(2015), the authors have initially applied sensors
and controllers to monitor the parameters of the
pond environment; however, the results are
limited in monitoring some parameters such as
temperature, pH, and light intensity. The very
important DO concentration was missing in their
work. Moreover, the results have not been
recorded and there have been no timely warnings
to farmers when pond water quality indicators
fall below threshold limits.
Materials to design an automatic system of
measuring and monitoring parameters in
aquaculture ponds
Sensors used to measure parameters in
aquaculture ponds
DS18B20 temperature sensor
To measure water temperature in
aquaculture ponds, we used the DS18B20 sensor
as shown in Figure 3. This is a MAXIM high
resolution (12bit) temperature sensor, capable of
Water resistant, with stainless compact design.
The construction consists of a transducer
immersed in water and an output consisting of 3
pins directly connected to the central control
board.
The above limitations motivated us to
conduct our study. The aim of our work was to
apply Internet of Things in measuring important
indicators of the pond environment automatically
and continuously. More specifically, in our
system, DO, pH, and pond temperature are stored
and transmitted wirelessly to smart devices
Specifications
Vietnam Journal of Agricultural Sciences
626
Nguyen Quang Huy et al. (2020)
Power input: 3.0 to 5.5V
pH sensor
To measure the pH level of the water in the
ponds, we used the pH sensor module V1.1 of
Gizmo Mechatronix central as presented in
Figure 4. The main construction of the sensor
consists of a pH probe and a signal conditioning
board which gives an output that is proportional
to the pH value and can be interfaced directly
with any Micro-controller.
Usable temperature range: -55 to 125°C (-67
to +257°F)
Accuracy: ±0.5°C accuracy from -10 to
+85°C
Selectable resolution: 9-12 bits
Query time: less than 750ms
Diameter of the tube: 6mm
Specifications
Communication: 1-Wire interface- requires
only one digital pin
Power Input: 5VDC
Working Current: 5 to 10mA
Power Consumption: 0.5W
Output: 3 wires - Red connects to 3-5V,
Black connects to ground, and Yellow is for data
DISSOLVED
OXYGEN
SENSOR
TEMPERATURE
SENSOR
pH-
SENSOR
INTERMEDIATE
RELAY
MODULE SIM
900A
THE CENTRAL CONTROL
BOARD ARDUINO NANO
RASPBERRY PI 3
DISSOLVED
OXYGEN AERATOR
WEB SERVER
SMART PHONE
COMPUTER
Figure 2. Structure diagram of the automatic system of measuring and monitoring parameters in aquaculture ponds
Figure 3. The DS18B20 temperature sensor (Getblocky, 2020)
627
Application of the Internet of Things technology in designing an automatic water quality monitoring system for aquaculture ponds
Response time: 5s
response time is 90s, the working pressure range
is 0-50Psi, and the connecting cable length is 2m.
The second one is a 42x32mm signal converter
board which is plug and play and has good
compatibility. It can be easily integrated into any
control or detecting system, the operating voltage
is 3.3-5V, an the output signal is 0-3V.
Detection Concentration Range: 0 to 14
Output: Analog
PCB Dimensions: 42 x 32mm
Working Temperature: -10 to +50oC.
Dissolved Oxygen (DO) sensor
Central control board
The DO indicator in water plays a vital role
in the development of aquatic animals. To
measure this indicator, we used DO sensor
module SKU SEN0237 developed by DFRobot
as shown in Figure 5.
The central control board receives data from
the sensors, implements control algorithms, and
communicates with modules such as Raspberry
and sim module. In our work, we use the Arduino
Nano board. It is a small, complete, and
breadboard-friendly board based on the
microcontroller ATmega328P (Arduino Nano
3.x). It offers similar connectivity and
works with a Mini-B USB cable instead of a
There are two main components of this
sensor. The first one is a galvanic probe, no need
for polarization time, and stays available at any
time. The filling solution and membrane cap are
replaceable, meaning low maintenance costs.
The DO measuring range is 0-20 mg L-1, the
Figure 4. The pH sensor (Bo-cam-bien-do-do-ph-6060476, 2020)
Figure 5. The Dissolved Oxygen (DO) sensor (mlab, 2020)
Vietnam Journal of Agricultural Sciences
628
Nguyen Quang Huy et al. (2020)
The Raspberry Pi 3 Model B+, as in Figure
6, is the latest product in the Raspberry Pi 3
range, boasting a 64-bit quad-core processor
running at 1.4GHz, dual-band 2.4GHz and 5GHz
wireless LAN, Bluetooth 4.2/BLE, faster
Ethernet, and PoE capability via a separate PoE
HAT.
standard one. Arduino Nano uses the CH340 chip
to convert from USB to UART instead of using
ATmega16U2 chip to simulate COM port as on
Arduino Uno or Arduino Mega. Thus, the
product costs are reduced while the main features
and functions of the other boards are kept and the
communication and programming of an Arduino
Nano board can be performed easily.
SIM 900 A module
Specifications
The process of sending a warning message
to the farmer when the DO level in the pond fell
below the threshold limits was carried out via
SIM 900A module. It has basic features like a
cell phone including calling, sending SMS, and
accessing GPRS. Due to its high stability,
simplicity of use, and 5VDC standard operating
voltage. Figure 7 illustrates Sim 900 A module
with the diagram of pins connected to the
Arduino Nano central board.
Microcontroller: ATmega328P
Communication chip: CH340 USB-Serial
Operating Voltage: 5V
Digital I/O Pins: 22 (6 of which are PWM)
Analog IN Pins: 8
DC Current per I/O Pins: 40mA (I/O Pins)
SRAM: 2KB
EEPROM: 1KB
Dissolved Oxygen aerator
Clock Speed: 16MHz
To provide DO for a 0.45-m3 tank, we used
the Mini Pump with 5-12V MB385, the capacity
of 12W, the flow of 4-5 L/Minute. This pump
was controlled via an intermediate relay.
Raspberry Pi 3 Model B+ module
The data of temperature, pH, and DO were
processed according to the programming
algorithm at the central control board and then
sent to the Raspberry Pi 3 B+ module. Here the
data continued to be processed and sent to the
cloud where it was stored in either a private or a
public channel, from which they would be stored
and observed via computers and smartphones
using the ThingSpeak platform.
Methods
Algorithm flowchart of the automatic
control system for measuring and monitoring
aquaculture pond parameters
The Algorithm flowchart of the system of
automatically measuring and monitoring the
Figure 6. Module Raspberry Pi 3 B+ (Raspberrypi, 2020).
629
Application of the Internet of Things technology in designing an automatic water quality monitoring system for aquaculture ponds
parameters of aquaculture ponds is presented in
Figure 8. The water quality indicators of the
ponds, including temperature, pH, and DO
levels, were measured by the sensors, and then
sent to the processor by the Arduino Nano
controller chip. Here, we set the DO threshold
limits at 2.0 mg L-1, if the DO level of the pond
fell below 2.0 mg L-1, it would turn on the oxygen
aerator to provide in-time with the amount of DO
for the pond, and through the SIM 900A module,
a warning message would be immediately sent to
the farmer's phone. The temperature, pH, and DO
data were stored and pushed to the Cloud via the
Raspberry Pi module. Farmers could use
Thingspeak software installed on phones or
computers to track and monitor these indicators
continuously.
provides a full range DO readings from 0 to
19.9 mg L-1 with ±1.5% accuracy.
The pH meter: HI8314 type made by Hanna.
It provides a full range of pH measurement
from 0 to 14 with ±0.01pH accuracy.
The results are presented in Tables 2, 3, and
4. To achieve these results, we operated the
system and conducted measurements 5 times per
hour. The system can perform the measurement
of parameters, viz. temperature, pH, and DO of
the ponds, continuously in a long time.
Tracking and monitoring parameters in
aquaculture ponds via computer or
Smartphone
By using the open-source ThingSpeak data
transfer platform, we were able to track and
monitor the parameters in aquaculture ponds
including temperature, pH, and DO indicators
through computers or Smartphones. The users
need a smart device (either smartphone or
computer) that is connected to the internet. Then,
one can access the ThingSpeak website and use
the previously registered account and password
to track the parameters of aquaculture ponds.
During the process, if the DO level in the pond
falls below the threshold level, the system will
send a warning message to the farmer and turn on
the aerator to provide oxygen to the pond.
Figures 9 and 10 below illustrate the process of
tracking and monitoring parameters on a
computer and sending warning messages to
farmers. To receive the warning messages, the
Results and Discussion
Measurement results of temperature, pH, and
DO concentration
To show the effectiveness of our system, we
compared our measurement results and reference
samples by the following standard machines:
The water temperature meter: DYS HDT-10
type made by EMIN, Korea. It measurres
temperature range from -50oC to +300oC
with ±1oC accuracy. This temperature meter
meets the EC No. E8 04 08 53916 001
quality certification.
The DO meter: DO Hanna HI9142 type
made by Hanna Romania. The meter
Figure 7. SIM 900 A module module (Arduino, 2020)
Vietnam Journal of Agricultural Sciences
630
Nguyen Quang Huy et al. (2020)
Start
Declarations of
temp = 0, oxy = 0, pH = 0
Sensor results read
temp = temperature, oxy =dissolved oxygen, and
pH = pH level
Turn off the DO
aerator
Oxy < 2.0 mg L-1
Turn on the DO
aerator
Sending the warning
messages to cell phones
Sending data of temperature, pH, and
dissolved oxygen to Raspberry Pi 3 and
transferring data to a Web server
End
Figure 8. The Algorithm flowchart of the automatic system for measuring and monitoring parameters in aquaculture ponds
phone number of the user needs to be added into
the coding for SIM 900 A Module. Then, the user
needs to maintain monthly payments to keep the
SIM 900 A active.
measurement of DO was quite accurate with the
maximum relative error of 2.88%.
From the discussions above, we can see that
by using this sytem, the users could actively track
and monitor the parameters of the aquaculture
ponds such as temperature, pH, and DO
concentration through smartphones or computers
with internet access. All these parameters were
stored in the system, and when the important
index of DO in the pond fell below the specified
level, there would be a warning message sent to
the farmer so that a method could be applied to
It can be seen that the system operated
according to the requirements. The temperature,
pH, and DO indicators of the ponds were
continuously measured, stored, and transmitted
to the network. The maximum relative error of
the result when compared to the sample
measuring devices was 3.57%, which was still
lower than the limit value of 5%. The
631
Application of the Internet of Things technology in designing an automatic water quality monitoring system for aquaculture ponds
increase the DO level. In this case, the dissolved
aerator machine would be turned on to timely
provide DO to the pond. This is the main
advantage of our system in comparison with the
works of Duy et al. (2015) or Binh & Tri (2016).
field of aquaculture. It not only helps to reduce
the time and effort of the farmers significantly
but also helps to improve aquaculture’s
productivity. In the near future, more research is
needed to develop the system to measure more
water quality parameters such as turbidity,
ammonia (NH3), and hydrogen sulfide (H2S) and
to employ solar energy for the operation of the
system.
Conclusions
In this work, we presented the design of an
automatic system for measuring and monitoring
water quality indicators of aquaculture ponds,
including temperature, pH, and DO. The test
results showed that the system achieved accuracy
in measuring temperature, pH, and DO, and was
reliable and easy to use. The autonomic system is
an important application of IoT technology in the
Acknowledgements
This work was supported by the ARES
Programwith Vietnam National University of
Agriculture [grant number T2019-09-24VB].
Table 2. Comparison of temperature results
Results by the system
Results by the standard machines
(oC)
Relative Error
(%)
Measurement times
(oC)
1
15.6
15.9
1.88
2
3
4
5
17.8
20.8
22.2
29.7
18.3
21.4
22.9
30.8
2.73
2.8
3.05
3.57
Table 3. Comparison of pH level results
Results by the system
(mol L-1)
Results by the standard machines
(mol L-1)
Relative Error
(%)
Measurement times
1
2
3
4
5
7.8
7.9
7.8
7.7
8.0
7.8
7.8
7.8
7.8
7.8
0
1.28
0
1.28
2.56
Table 4. Comparison of DO results
Results by the system
Results by the standard machines
(mg L-1)
Relative Error
(%)
Measurement times
(mg L-1)
1
2
3
4
5
10.2
10.4
10.4
10.4
10.4
10.4
1.92
2.88
1.92
2.88
0.96
10.7
10.6
10.7
10.5
Vietnam Journal of Agricultural Sciences
632
Nguyen Quang Huy et al. (2020)
Figure 9. Tracking and monitoring temperature, pH level, and dissolved oxygen indicators through a computer
633
Application of the Internet of Things technology in designing an automatic water quality monitoring system for aquaculture ponds
Figure 10. Warning messages sent to farmers when the dissolved oxygen drops below the threshold level
Liu X. (2015). Traceability system design for fruits and
References
vegetables safety based on internet of things
Akhmetov B. & Aitimov M. (2015). Data Collection and
Analysis Using the Mobile Application for
Environmental Monitoring. Procedia Computer
Science. 56: 532-537.
technology. Advance Journal of Food Science and
Technology. 8(10): 711-715.
Ran N. (2014). Design and implementation of intelligent
greenhouses based on the internet of things. Applied
Mechanics and Materials. 188-191.
Athanasios S. V., Charalampos Z. P., Alexander B. S.,
Vasileios A. N. & Eftychia M. X. (2010). A complete
farm management system based on animal
identification using RFID technology. Computers and
Electronics in Agriculture. 70: 380-388.
Vietnam Association of Seafood Exporters and
Proceducers (2020). Overview of Vietnam's seafood
industry in 2019. Retrieved on February 3, 2020 from
nganh.htm (in Vietnamese).
Binh D. T. & Tri V. M. (2016). 3D field model of
environmental parameters for aquaculture pond.
Science Magazine. Can Tho University. 102-108.
Vietnam Fisheries Society (2018). Solution of stabilizing
dissolved oxygen index in ponds. Retrieved on
Duy N. T. K., Tu N. D., Son T. H. & Khanh L. H. D. (2015).
Automated monitoring and control system for shrimp
January
20,
2020
from
farms
based on embedded system and wireless
hoa-tan-trong-ao-article-20999.tsvn (in Vietnamese).
sensor network. In Electrical, Computer and
Communication Technologies (ICECCT), 2015 IEEE
International Conference. 1-5.
Some types of equipment for measuring dissolved oxygen
in aquaculture ponds (2020). [Picture of Some types of
equipment for measuring dissolved oxygen in
aquaculture ponds] [Photograph]. Some types of
equipment for measuring dissolved oxygen in
aquaculture ponds. Retrieved on March 5, 2020
General Department of Fisheries (2019). Seafood exports
reached a record of 9 billion USD in 2018. Retrieved
on
February
3,
2020
from
301242.html (in Vietnamese).
The DS18B20 temperature sensor (2020). [The DS18B20
temperature sensor] [Photograph]. The DS18B20
temperature sensor. Retrieved on February 3, 2020
Lin H., Cai K., Chen H. & Zeng Z. F. (2015). The
construction of a precise agricultural information
system based on internet of things. International
Journal of Online Engineering. 11(6): 10-15.
Vietnam Journal of Agricultural Sciences
634
Nguyen Quang Huy et al. (2020)
The pH sensor (2020). [The pH sensor] [Photograph]. The
pH sensor. Retrieved on February 4, 2020 from
B+] [Photograph]. Module Raspberry Pi 3 B+.
Retrieved
on
February
5,
2020
The Dissolved Oxygen (DO) sensor (2020). [The Dissolved
Oxygen (DO) sensor] [Photograph]. The Dissolved
Oxygen (DO) sensor. Retrieved on February 5, 2020
Module Sim 900 A (2020). [Module sim 900 A]
[Photograph]. Module sim 900 A. Retrieved on
February 6, 2020 from http://arduino.vn/bai-viet/851-
Module Raspberry Pi 3 B+ (2020). [Module Raspberry Pi 3
635
12 trang
22/04/2022
340
Bạn đang xem tài liệu "Application of the internet of things technology (IoT) in designing an automatic water quality monitoring system for aquaculture ponds", để tải tài liệu gốc về máy hãy click vào nút Download ở trên
File đính kèm:
- application_of_the_internet_of_things_technology_iot_in_desi.pdf
