Development of a Water Quality Control System for Catfish Cultivation Using the Fuzzy Logic Method with IoT-Based Monitoring

Abstract

Catfish (Clarias spp.) is a freshwater species known for its resilience to murky water conditions. However, when the water quality deteriorates excessively, it can become a breeding ground for diseases that hinder fish growth and even lead to mortality. Consequently, regular water changes are crucial to maintaining optimal conditions for fish cultivation. In response to this issue, this study proposes the development of an automated monitoring and control system to help manage water quality in aquaculture systems. The system integrates various sensors, including pH, DS18B20 temperature, HC-SR04 distance, turbidity, and MQ-135 air quality sensors, along with a Wemos D1 R32 microcontroller, water pump, servo motor, and an ESP-32 camera for real-time monitoring. An Android application is used to facilitate manual or automatic control of the system. The fuzzy logic method is employed to maintain optimal water quality parameters, with target values for temperature between 27-29°C, pH between 6.5-8.5, and turbidity below 32 NTU. System tests revealed that reducing the water temperature from 34°C to the target range of 27-29°C took 180 minutes, while stabilizing the pH from 9 to the optimal range (6.5-8) also took 180 minutes. Similarly, it took 187 minutes to reduce turbidity from 40.3 NTU to below 32 NTU. The results from Android-based monitoring and control tests showed that nearly all trials were successfully conducted. This research contributes significantly to the development of IoT-based automation in aquaculture, particularly in water quality control, offering a reliable and efficient solution to enhance the sustainability of catfish farming practices.