The IoT-Based Water Quality Monitoring System for Fish Ponds Using Fuzzy Inference Method

Internet of Things (IoT) system for monitoring fish pond water quality using the fuzzy inference method

Abstract

This study develops an Internet of Things (IoT) system for monitoring fish pond water quality using the fuzzy inference method. The system utilizes pH, Total Dissolved Solids (TDS) and temperature sensors to measure water quality parameters that are crucial for fish health. Data from the sensor is diffused to produce more easily understood information about water quality conditions. The Arduino Nano serves as the main microcontroller processing sensor data, while the ESP8266 module is utilized for Wi-Fi connections for real-time monitoring via thinger.io web-based applications. Prior to testing, the sensor has been calibrated to ensure measurement accuracy with commercially available measuring instruments. And the test results on three water samples—tap water, tilapia pond water, and mujair pond water—showed high accuracy with consistent results. The Fuzzification results of IoT devices can be close to the test results of Simulink Fuzzy on each sample, with different

KEYWORDS: IoT, water quality, fuzzy inference, pH sensors, TDS.