IoT-Based Water Quality Monitoring and Control System for Koi Fish Ponds - Adriansyah, Agil Yafi; Ningrum, Novita Kurnia (Journal of Applied Informatics and Computing, 2026)
Koi fish (Cyprinus rubrofuscus) require stable water quality to support their health and growth, yet conventional pond water management is generally performed manually and tends to be inefficient and inconsistent. This study aims to design and implement an Internet of Things (IoT)-based water quality monitoring and control system for koi fish ponds. The proposed system integrates an ESP32 microcontroller with pH, turbidity, ultrasonic, and water level sensors to monitor pond conditions in real time and support controlled water drainage and refilling through a web-based interface. Sensor data are transmitted to Firebase Cloud, enabling remote monitoring and control via an internet connection. System testing was conducted on four koi ponds with ten measurements for each parameter, resulting in forty data samples per parameter. The experimental results show that the sensors provide stable measurements with average error values below 3%, and the system demonstrates a response time of approximately 1–2 seconds under stable network conditions. These results indicate that the developed system is capable of supporting effective water quality monitoring and control while reducing reliance on continuous manual supervision in koi pond management.