Implementation of a Web-Based Water Quality Control System for Koi Ponds Using Mamdani Fuzzy Logic and the Laravel Framework

Abstract

This study presents the design and implementation of a web-based water quality control system for koi ponds using Mamdani fuzzy logic and the Laravel framework. The system integrates pH, TDS, and temperature sensors with an ESP32 microcontroller to monitor water conditions in real-time. The fuzzy logic controller processes sensor inputs and automatically activates pumps to inject acid or base solutions, thereby maintaining optimal water quality. Test results show that the pH sensor achieved an average accuracy of 95.27% with an error rate of 4.73%, while the TDS and temperature sensors recorded accuracies of 97.95% and 98.35%, respectively. The fuzzy control system demonstrated a very low error rate of 0.93%, ensuring precise decision-making. The Laravel-based web application successfully displayed and recorded monitoring data with only a 1–2 second delay, providing a user-friendly interface for farmers. Overall, the system effectively improves aquaculture productivity and reduces the risk of fish mortality by offering automated and accurate water quality management.