Telementry System Design for Fish Pond Water Quality Monitoring

Based on Internet of Things

Danuri and M. Asep Subandri

Department of Informatics, Politeknik Negeri Bengkalis Jl. Bathin Alam, Sungai Alam, Bengkalis, Riau, 28711, Indonesia

Keywords: Water, IoT, Telementry.

Abstract: Water quality is the main parameter in the success of fish farming. As a place for fish to live, changes in the

physical parameters of water can directly affect the growth and survival of fish. Therefore, fish farmers need

to make regular observations of the condition of the water in aquaculture ponds and then provide certain

treatments so that the water conditions remain in accordance with the prerequisites for the growth and

development of the cultivated fish. Fish farmers observe water conditions by taking pond water samples to be

observed in the laboratory or using handheld sensor equipment. This mechanism requires a lot of time and

money. In addition, it also requires the presence of farmers continuously in the cultivation pond, which of

course makes it difficult for farmers, especially if the size of the cultivation pond is large. In this study, a

water quality monitoring system for freshwater aquaculture ponds based on Internet of Things (IoT)

technology was designed. The working principle of the system is to send data from several water quality

sensors (pH, turbidity, temperature, salinity, and water level) through an embedded system to a cloud service.

Fish farmers then can monitor pond water quality using their PC/smartphone. The main contributions of this

article are: propose an integrated system with weather forecast services and telegram message notifications.

1 INTRODUCTION

Indonesia is a maritime country consisting of

thousands of islands with an area of 3977 miles

between the Indian Ocean and the Pacific Ocean. Of

this area, 75% is ocean and 25% is land. With these

geographical conditions, the fishery sector is one of

the potential sectors to support the Indonesian

economy (Junaidi & Kartiko, 2020). The fairly high

demand by neighboring countries such as Malaysia,

Singapore, Japan and China for various types of

consumption fish should be a great opportunity for

Indonesian fishermen and the fishing industry to meet

the market demand. Domestically, based on data

released by the Ministry of Maritime Affairs and

Fisheries of the Republic of Indonesia, the level of

fish consumption rose from 47.34 kg/capita/year in

2017 to 54.50 kg/capita/year in 2019. In 2021, this

figure will increase to 55.56 kg/capita/year, and is

projected to continue increased in the following years

(Perikanan, 2022). In terms of potential employment,

the aquaculture sector in 2030 is projected to create

8.9 million new jobs, which is an increase from the

current figure of 2.7 million jobs (Phillips et al.,

2016).

The increase in the fisheries sector in Indonesia

has not been matched by the development of adequate

science and technology. For example, in cultivating

fish, many farmers do not know the cause of the

sudden death of fish. The main factor that determines

the success of fish farming is water quality. Physical

parameters that can be observed to describe water

quality include temperature, acidity (pH), dissolved

oxygen and salt levels (Chien, 1992). As a place for

fish to live, changes in these physical parameters can

directly affect the growth and survival of cultivated

fish (Junaidi & Kartiko, 2020; Manoj et al., 2022).

Each type of cultivated fish has different prerequisites

for water conditions in order to grow optimally. Fish

will live and breed well if the environmental

conditions provided in accordance with their living

conditions can be met or close to their natural habitat.

Therefore, fish farmers need to make regular

observations of the condition of the water in

aquaculture ponds and then provide certain

treatments so that the water conditions remain in

accordance with the prerequisites for the growth and

development of the fish being cultivated.

The results of the study show that about 60% -

70% of the causes of dead fish in aquaculture are

Danuri, . and Subandri, M.

Telementry System Design for Fish Pond Water Quality Monitoring Based on Internet of Things.

DOI: 10.5220/0011843100003575

In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2022), pages 573-576

ISBN: 978-989-758-619-4; ISSN: 2975-8246

573

caused by poor observations of water quality (Boyd,

1990). About 80% of aquaculture still uses manual

methods in observing water quality (Lannan et al.,

1986). Water quality cannot be observed with the

naked eye, to make observations, farmers take

aquaculture pond water samples and then take them

to the laboratory or use handheld sensor equipment.

This mechanism requires the presence of farmers

periodically in fish farming ponds. In addition, it also

takes a long time and costs a lot (Ismail et al., 2020;

Manoj et al., 2022). For laboratory tests, the costs

range from Rp. 10,000/parameter/one test to Rp.

200,000/parameter/one test. While handheld sensor

equipment, prices start from Rp. 1,500,000 to Rp.

7,000,000 per test parameter.

Based on these problems, the authors propose a

design of a water quality monitoring system for

aquaculture ponds that can transmit data on physical

parameters of water quality in real time without

requiring the presence of farmers around the pond.

Parameters observed consisted of pH, turbidity,

temperature, salinity, and water level. This system

will also utilize data from weather forecast service

providers, because rainwater is indicated affect water

quality. In addition, there is a warning notification

feature if the water condition crosses the safe

threshold if the farmer does not want to check the

PC/smartphone regularly.

2 DESIGN

Based on previous research, there are several

shortcomings, including: the average water quality

monitoring system only uses one node, the physical

parameters used to measure water quality are few, the

protocol has not used a low size and bandwidth

efficient protocol, the data obtained is not stored and

processed, then no integration with other service

providers. In this study, a water quality monitoring

system for fishpond was designed that could be

developed in terms of quantity (scalable). The

prototype of the device to measure the physical

parameters of the water quality of aquaculture ponds

in this study also uses a more complete sensor. This

system uses the MQTT protocol to be able to transmit

data in real time. This protocol is known to be suitable

for devices with limited capabilities (embedded) and

efficient communication of power and bandwidth.

Then, not only monitoring, the measurement data can

also be stored for big data purposes. In addition, the

system is designed to be able to connect with other

service providers such as weather forecasting,

messaging, and others. The system architecture

design proposed in this study can be seen in Figure 1

below.

Figure 1: Architecture of Fishpond Water Quality

Monitoring.

The proposed monitoring system consists of three

main parts: a collection of sensor nodes, a router/hub

device and a cloud service. The following is an

explanation of each of these sections.

2.1 Sensor Node

The sensor node is a device that observe the physical

parameters of fishpond water. This device is placed

directly on the observed pool object. Broadly

speaking, this device is composed of three

components, namely: a microcontroller as a

computing device, a sensor to observe the physical

parameters of water and a communication module to

transmit the observed data to the gateway device. The

design of the device can be seen in the image below.

Figure 2: Sensor Node Component.

To be able to measure temperature, author uses

the DS18B20 sensor, measures distance using the

SR04 ultrasonic sensor, measures water clarity using

a turbidity sensor, measures salt levels using a

conductivity / salinity / TDS sensor, and to measure

the degree of acidity or base using a pH meter sensor.

Meanwhile, to transmit measurement data, the author

uses the ESP8266 wifi module.

iCAST-ES 2022 - International Conference on Applied Science and Technology on Engineering Science

574

2.2 Router/Hub

This device has a role to receive data from

observations of the condition of aquaculture pond

water from all sensor node devices. The data is then

sent to the cloud via the internet for further data

processing and presentation.

2.3 Cloud/Service

This section has a role to collect, store and process

data from observations of physical parameters of

fishpond water. The data that has been stored and

processed can then be accessed by fish farmers

through a web-based application. Not only that, the

application is integrated with weather forecast

services and message notification services. The

following is a design view of the application to be

built.

Figure 3: Web Application to Monitor Water Quality.

3 METHOD

The internet of things-based telemetry system for

monitoring fishpond water quality was developed

using a prototyping methodology. Protoyping is a

methodology in which an initial prototype with the

main functionality is built, then presented to the user,

the user then provides input so that the resulting

device is truly in accordance with the wishes and

needs of the user (Despa, 2014). Figure 4 below

shows the flow.

Figure 4: Prototyping Methodology Steps.

Changes and presentation of the prototype can be

done many times until an agreement is reached on the

form of the software to be developed. The advantages

of the prototyping methodology are: it is best when

goal is not well understood, it is useful when client is

not technically not well, requirement may be added

while developing software, and it is most flexible

model for developing software (Chandra, 2015).

4 CONCLUSIONS

The design of fishpond monitoring and measurement

system using an IoT is designed and proposed to

assist fishpond farmers in monitoring the water

quality of their ponds. This model is intended to

alleviate the problems through manual monitoring,

such as tedious testing and exhaustive inspection due

to wet and spacious farming. Benefit from using the

proposed model includes more effective monitoring

of the fishpond as the system can monitor the quality

of the water in a timely manner and alert the fish

farmers to detect water quality degradation. In this

model, five parameters can be monitored, which are

water temperature, pH, water level, turbidity, and

salinity. With the help of the proposed design, the

quality of water can be continuously measured and

monitored to ensure the growth and survival of fish in

ponds. As a result, preventive action can be taken in

a timely manner to minimize losses and increase

productivity.

The purpose of this study was to propose a model

of fishpond water quality measurement and

monitoring system based on the Internet of Things

(IoT) in order for fishpond farmers to monitor the

water quality of their ponds. Therefore, our future

work will be to focus on the implementation of the

system. Furthermore, the collected data can be

analyzed using big data analytics, and preventive

measures can be taken before the threshold range is

crossed by the water quality parameter.

ACKNOWLEDGEMENTS

This research was supported by Pusat Penelitian dan

Pengabdian Kepada Masyarakat (P3M) Politeknik

Negeri Bengkalis on Scheme Applied Research.

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