Microcontroller-Based Water Quality Monitoring System Implementation

Abstract

So far, Regional Drinking Water Companies (PDAMs) have used conventional methods by taking water samples, measuring all water quality parameters, and analyzing them one by one. In addition, the process of making conclusions on water quality has not been integrated so that it can cause misclassification of water quality and prolong the work. In this study, an expert system was designed to monitor water quality that works in real time so that it can be accessed anytime and anywhere. The water quality analysis process is carried out with a fuzzy classifier realized using Arduino Mega 2560. The fuzzy input variables include the pH value, total dissolved solids (TDS), and turbidity or turbidity. A fuzzy inference system is used to classify water quality into three classes, namely good (meets quality standards), ordinary, and bad (polluted). The expert system of success provides inference results with a 100% success percentage. The results of monitoring and water quality classification can be accessed online using the Internet of Things (IoT) ThingSpeak platform