Biofloc Water Quality Measurement for Catfish Farming at the Green House Area

Abstract

Biofloc technology is widely used in aquaculture due to its efficiency in maintaining water quality and fish health. However, manual monitoring of water parameters remains a challenge for fish farmers. The purpose of this study is to design and implement an Internet of Things (IoT)-based water quality monitoring system specifically for the production of biofloc catfish in the Green House area of Telkom University. The system utilizes an ESP32 microcontroller and three sensors: DS18B20 for temperature, PH-4502C for pH, and SEN0189 for turbidity. Data collected from the sensors are transmitted to the Firebase real-time database and visualized on a web application featuring a dashboard, charts, and gauges. The system was tested over several weeks to evaluate its performance in capturing environmental changes. The results show that the system successfully recorded real-time data and classified the water quality status on the basis of predefined thresholds. The monitoring platform proved to be responsive, accurate, and practical for continuous use in aquaculture environments. In conclusion, the proposed system supports smart aquaculture by allowing farmers to take immediate action to maintain ideal water conditions, thus improving operational efficiency and reducing potential losses.