IoT-based Water Quality Control in Tilapia Aquaculture Using Fuzzy Logic

Tilapia (Oreochromis niloticus) is a prominent species in freshwater aquaculture due to its high protein content and economic value. Maintaining optimal water quality is crucial for the health and growth of tilapia, particularly in terms of pH levels. Deviations in pH, whether too acidic or too alkaline, can lead to decreased appetite and increased mortality rates in tilapia. The objective of this study is to design an intelligent control system to monitor and regulate the pH and temperature of tilapia aquaculture ponds using the Sugeno Fuzzy method integrated with Internet of Things (IoT) technology. The system employs DS18B20 temperature sensors and E-201-C pH sensors to collect real-time data on pond conditions. The data are then processed by an ESP32 microcontroller, which employs Sugeno Fuzzy logic to determine the appropriate adjustments to be made. The system administers pH buffers to maintain the water within the optimal pH range. Furthermore, the collected data are transmitted to a web server, enabling real-time monitoring and analysis. The findings indicate that the proposed IoT-based system is effective in maintaining water quality, ensuring that the pH and temperature levels remain within the ideal range for tilapia. This study demonstrates the potential of integrating IoT and Sugeno Fuzzy logic to provide a robust solution for managing water quality in aquaculture settings, enhancing the sustainability and productivity of tilapia farming.