Development of Water Quality Monitoring Systems

in Super Intensive Aquaculture System

using ESP32 and Blynk

Murie Dwiyaniti

, Rika Novita W.

and Tohazen

Electrical Engineering, Politeknik Negeri Jakarta, Indonesia

Keywords: Water quality, real-time monitoring, IoT, ESP32, Blynk

Abstract: Best water quality is the most important medium to optimize fish growth in a super-intensive aquaculture

system. Any changes in the parameter of water will affect fish growth and even will cause death. For this

reason, parameters of water quality should be monitored in real-time and automatically send the data to the

owner based on the internet of things (IoT). So that the owner will know all data in real-time and does not

need to be located in the pond all day. The owner can simply look at the data on the smartphone. So working

time becomes more efficient. In this study, we developed a water quality monitoring integrated, consist of (1)

sensors: dissolved oxygen (DO) temperature, pH, and salinity; (2) ESP32 and ADS115 microcontrollers as

controllers and ADCs; (3) display of parameter values based on IoT with the Blynk platform. This system can

measure water conditions in real-time, display parameter values via a smartphone, and send notifications or

alarms if there is a change in value, exceed the specified threshold. The test results show that this system can

receive and send data to the Blynk application; alarm gives notification on the smartphone in the event of

reading the parameter values exceed the specified threshold.

1 INTRODUCTION

Aquaculture is an up-and-coming food production

sector. Business projections in Indonesia indicate that

aquaculture will grow to more than 10.1 tons per year,

creating 8.9 million jobs equivalent to full-time

employment in production and will become a sector

with a production value of USD 39.5 billion by 2030

(Phillips et al., 2016). Indonesian aquaculture

production includes seaweed, tilapia, catfish,

milkfish, shrimp, and tuna. However, to produce high

quality of aquaculture production need good water

quality. Parameter of water that affects fish growth is

dissolved oxygen (DO), temperature, pH, and salinity

(Wiranto & Hermida, 2010).

Changes in water quality parameters such as

changes in temperature will cause decreased appetite

and many calories lost, which can cause death (Fuady

& Nitisupardjo, 2013). Avery changes in water

quality parameters outside the standard have an

impact on the pattern of life, and its development

even can cause death. Therefore, it is necessary to

measure water quality in real-time and control

parameters so that they remain constant within the

allowable value.

Water quality management and monitoring

systems in aquaculture have been investigated with

various method of data reading using Arduino

(Anwar, Hermida, & Waslaluddin, 2018; Hongpin,

Guanglin, Weifeng, Jie, & Qiuwei, 2015; Multazam

& Hasanuddin, 2017; Sambora & Waluyanti, 2016;

Wiranto & Hermida, 2010). However, Raspberry Pi

is a lot more advanced compared with Arduino

because it has an intrinsic Wi-Fi module (Ferdoush &

Li, 2014). The continuously detected information is

sent directly to the owner through app/Android

(Hongpin et al., 2015; Kusrini, Wiranto, Syamsu, &

Hasanah, 2016). Recently IoT is reaching the top

level to the monitored parameter of water quality

(Abinaya, Ishwarya, & Maheswari, 2019; Chavan,

Patil, Chavan, Sana, & Shinde, 2018; Encinas, Ruiz,

Cortez, & Espinoza, 2017; Niswar et al., 2018;

Nocheski & Naumoski, 2018; Zhang, Hua, & Wang,

2013). However, for a case of water quality in super-

intensive aquaculture, controlling and monitoring

using ESP32 microcontroller connected to ADS115

based on the Blynk platform almost not found.

Dwiyaniti, M., W., R. and Tohazen, .

Development of Water Quality Monitor ing Systems in Super Intensive Aquaculture System using ESP32 and Blynk.

DOI: 10.5220/0009894200002905

In Proceedings of the 8th Annual Southeast Asian International Seminar (ASAIS 2019), pages 90-95

ISBN: 978-989-758-468-8

Therefore, this research made a system design

with the ESP32 controller integrated with ADS115

and data monitoring via the IoT Blynk platform. In

this system, there is also an alarm that can provide

notification to the owner via a smartphone. If there is

a change in the parameter value that exceeds the

specified threshold. Also, the data recording for one

day will be sent to the owner via email.

2 METHODOLOGY

The research method consists of three parts, namely

(1) system architecture design; (2) manufacturing

hardware used for implementation; and (3) making

software that describes the functions of each

component.

2.1 System Architecture

Integrated components in this system are ESP32

module, ADC with ADS115 type, Sensor, database,

Blynk platform IoT Service, mobile application, and

Desktop application. Figure 1 shows the system

architecture: input, process, output, connectivity, and

data display.

WEB IoT

Broker IoT

Prototipe RTU berbasis mikrokontroler

Telah dibuat pada penelitian tahun 2015 - 2017

Multi Valve

Multi Pompa

Multi sensor

Input (sensor)

Figure 1: System architecture

In this section, there are four sensors used,

namely the LM35DZ temperature sensor, the

SEB0161-V2 pH sensor, the salinity sensor, and the

Atlas Dissolved Oxygen sensor. Temperature, pH,

and salinity sensors are connected with ADS115 to

convert analog data to digital then the data is read by

ESP32. Whereas the DO Sensor sends data via UART

(Universal Asynchronous Transmitter-Receiver) to

ESP32. Data measurement is done by immersing all

of these sensors into water.

Connectivity data from the sensor transmit via

Wi-Fi that is in ESP32. Wi-Fi on ESP32 works in the

2.4 GHz frequency band and transfers data up to 150

Mbit / s.

The ESP32 module is used as a controller for

receiving and sending data to the internet. Data from

the ESP32 module is displayed on Blynk, which is an

internet-based mobile OS application platform.

2.2 Hardware

As equipment storage, we use aluminum luggage

with a material thickness of 5 mm, outer size,

27x23x7cm, and inner size 26.5x1.5x6cm. In this

suitcase, consist of the component, as in Figure 2.

2.2.1 Power Module

The power module has a DC-DC converter, BMS

(batteries management system), and 25 units of Li-

Ion 18650 Cylindrical batteries with a capacity of

2700 mAh, 3.7V voltage connected in parallel. The

battery is used to supply control in the night as water

quality parameters, for the most part, changes at

night. A DC-DC converter use for convert voltage to

scale controller module, which will work at 5V.

2.2.2 Sensor Module

The sensor module consists of pH, temperature,

salinity, and DO sensors. These sensors are connected

with ESP32 for detecting the water parameters.

2.2.3 Controller Module

The most important part of this project is ESP32 RTU

modules as a controller. ESP32 is a low budget,

inbuilt Wi-Fi module, easy write and read data

programming with Arduino language, and sends that

data to IoT platform.

2.2.4 Output Module

The output module consists of a relay that connected

to the water pump and valve. The operation of the

relay depends on a signal from the controller.

2.2.5 Display

Smartphone and 7-inch screen size tablets are used to

the monitored parameter of water quality. An app of

the Blynk platform has been developed in these. If the

sensed data exceed the threshold ranges alert message

will be shown in the monitor.

Development of Water Quality Monitoring Systems in Super Intensive Aquaculture System using ESP32 and Blynk

Figure 2: Hardware in the aluminum suitcase

2.3 Software

This system uses ESP32 with the Arduino

programming language. We made programming of

reading serial sensor data, analog sensor data,

conversion of analog to digital data, connection to

Blynk, sending data to Blynk, as shown in the

flowchart of Figure 3.

Figure 3: Flowchart system

The flowchart in the software starts with the detection

of an internet connection. It must be connected to the

Blynk server. If there is an internet connection, the

sensor starts sending data, and ESP32 receives the

data to be forwarded to the Blynk server. After the

server on Blynk is updated, the data will be displayed

on the Blynk application on the smartphone.

3 RESULT AND DISCUSSION

A water quality monitoring system has been

developed successfully using hardware, software, and

architecture that have been designed. The experiment

was taken to a fishpond to test the performance of the

equipment of a water quality monitoring system.

Water quality parameters are set as follows:

1. The range of values for temperature = 27

C -

2. The range of values for PH = 5 - 8.0

3. The range of values for dissolved oxygen

(DO) = 4 - 10 mg / l

4. The range of values for salinity = 0 - 1 g / l

Figure 4 shows the system implementation. An

aluminum suitcase with four sensors and electronic

devices are placed near the pond where the water

quality will be measured, and four sensors immersed

in the pond. Implementation is started at 07.00 AM

until 09.00 PM.

Figure 4: Implementation system

ASAIS 2019 - Annual Southeast Asian International Seminar

This system has a current of 0.85 a, using a lithium-

ion battery of 13,500 mA/hour, the system is capable

of working around 114.75 hours. This is more than

enough to prove the concept of this prototype. The

measurement result can be seen in Figures 5, 6, 7, 8.

Figure 5: Data measurement from a salinity sensor

Figure 6: Data measurement from the DO sensor

Figure 7: Data measurement from temperature sensor

Figure 8: Data measurement from pH sensor

From figure 5-8, we can see that all of the

measurement was taken from 07.00 AM until 09.00

PM. All data are within the standard range of values:

salinity is 0-0,5 g/L, DO tends to be constant at 5

mg/L, the temperature in range 27

C-33

C, and PH

stable at 7.

These data send to IoT with the Blynk

platform every second. Display data in a smartphone

or tablet can be seen in Figure 9.

Figure 9: Display data in smartphone

Development of Water Quality Monitoring Systems in Super Intensive Aquaculture System using ESP32 and Blynk

From Figure 9, it can be seen that the data of each

sensor appears on the smartphone display. Also,

history data appears in graphical form. This data

history can be sent to the owner if needed via email

in the form of data.csv.

If there is a sensor reading condition exceed the

standard threshold, a notification will appear on the

smartphone, as shown in Figure 10.

Figure 10: Display of alert in smartphone

Figure 10 shows that the temperature that occurred

was 26.6

C. Because this temperature exceeds the

standard threshold, the notification "Temperature

low-low" appears. Similar to other parameters, if the

measurement exceeds the range of standard values,

this notification will show.

4 CONCLUSIONS

This study presents a prototype implementation of the

concept of a remote monitoring system with IoT

technology aimed at monitoring water quality in

aquaculture. The test results prove that the system has

worked well and able to measure the values of water

parameters such as pH, temperature, salinity, and DO.

ACKNOWLEDGEMENTS

This work was supported by Decentralization

Research “Skim Penelitian Produk Terapan” which is

the allocation for the Polytechnic State of Jakarta

under contract number: 221/PL3.18/SPK/2019.

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Development of Water Quality Monitoring Systems in Super Intensive Aquaculture System using ESP32 and Blynk