Simulation of Fuzzy Logic Implementation in an IoT-Enabled Water Quality Monitoring System Using ESP8266

Abstract

This paper presents the design and implementation of a fuzzy logic-based water quality monitoring system using the ESP8266 microcontroller and a set of environmental sensors. The system utilizes temperature, humidity, pH, and Total Dissolved Solids (TDS) as input parameters to assess water quality in real time. Each input is fuzzified into linguistic categories and processed through a fuzzy inference engine to produce a continuous water quality score aligned with WHO standards. The system is integrated with an IoT platform for remote monitoring. Simulation results demonstrate smooth transitions between membership functions and the model’s ability to handle overlapping conditions. For instance, at pH 7.5, the system outputs membership degrees of 0.83 in the "Good" set and 0.17 in the "Moderate" set, reflecting a chemically acceptable state. With sensor inputs of 28°C temperature, 65% humidity, pH 7.5, and 400 mg/L TDS, the system produces a water quality score of 12.6, indicating excellent quality. Field testing under various conditions and comparison with laboratory measurements show an accuracy of 92%. The fuzzy logic model offers more consistent classification than crisp thresholding, especially during transient changes or sensor drift. However, system accuracy heavily depends on proper sensor calibration, and the rule base must be adapted to regional standards. Additionally, real-time fuzzy computation on the ESP8266 is limited, requiring processing to be offloaded to MATLAB or cloud-based systems.