Optimization of Shrimp Cultivation Through Internet of Things-Based Water Quality Monitoring

Abstract

Shrimp farming is a highly profitable sector of the fishing industry. However, manual water
quality monitoring remains a barrier to improving farming efficiency. Manual monitoring not only requires
a large workforce, but is also prone to human error and is less responsive to changes in environmental
conditions. This study developed an Internet of Things (IoT)-based water quality monitoring system
capable of monitoring pond water quality parameters in real-time and efficiently. This system is equipped
with temperature sensors DS18B20, pH sensors, salinity sensors, turbidity sensors, and dissolved oxygen
(DO) sensors. The data from the sensor readings is sent to the server via the internet and displayed on the
monitoring website interface. The system is also integrated with Telegram notifications to provide early
warnings in the event of significant changes in water quality parameters. Test results show that this system
is capable of monitoring water quality accurately and in real-time, thereby reducing dependence on manual
labor. The data stored in the database can also be used for further analysis to improve shrimp farming
management and productivity.

Keywords: IoT, Shrimp Farm, Real-time Water Quality Monitoring, Telegram Notification Sensor, Shrimp Farming,
Fisheries Management.