IoT-Based Smart Aquarium Control System for Ornamental Fish Feeding and Water Quality using Fuzzy Mamdani

Abstract

The ornamental fish cultivation sector is highly dependent on efficient feeding management and stable water quality maintenance. One of the main problems frequently encountered is overfeeding, which leads to the accumulation of ammonia toxins and degradation of water quality that is difficult to monitor manually. This study aims to develop an Internet of Things (IoT)-based smart aquarium control system using the Fuzzy Logic Mamdani method. The system is designed to automate adaptive fish feeding and to maintain water quality in a proactive and sequential manner. The hardware components used include an ESP32 microcontroller, a temperature sensor (DS18B20), a pH sensor, a turbidity sensor, and a load cell sensor to monitor feed stock. Sensor data are transmitted to the cloud and can be monitored in real time through a web-based dashboard. The system integrates two Fuzzy Logic modules: the first module determines feeding duration based on fish type, fish size, number of fish, and water temperature, while the second module manages water quality by prioritizing turbidity detection before performing pH correction using a dosing pump. The test results indicate that the system is capable of reading sensor data accurately after calibration and successfully executing actuator actions according to the defined fuzzy rules. In conclusion, the proposed smart aquarium prototype has been successfully implemented and provides a more adaptive and efficient solution compared to conventional manual maintenance methods.