Siti Syahidatul Helma
Department of Information System, Politeknik Caltex Riau

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Implementation of Real-Time Drinking Water Quality Monitoring System Based on IoT Technology Ivan Chatisa; Siti Syahidatul Helma; Rayhan Aryapati
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 8 No 2 (2026): April 2026
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v8i2.2521

Abstract

Deterioration in drinking water quality is often difficult to detect visually because changes in physical and chemical parameters are not always immediately apparent. Water with high Total Dissolved Solids (TDS), abnormal pH values, or increased turbidity may pose health risks if consumed continuously. Therefore, a monitoring system is required to provide rapid and accurate information about water conditions. This study aims to develop an Internet of Things (IoT)-based drinking water quality monitoring system capable of real-time monitoring. The proposed system uses three main sensors pH, turbidity, and Total Dissolved Solids (TDS) to measure water acidity, turbidity, and dissolved solids content. Sensor data are processed using an ESP32 microcontroller and transmitted via the internet to a web-based dashboard, where the data are visualized in real-time graphs. The system also provides alert notifications through a Telegram bot when parameter values exceed the safe limits. Experimental results show that the system successfully monitors water quality in real time. Tests conducted on four water samples indicate that the TDS value of bottled water ranges from 119–130 ppm, while municipal water reaches 304.28 ppm, both below the 500 ppm threshold. The pH values range from 7.12 to 7.95, which remain within the standard range of 6.5–8.5. However, the turbidity of municipal water reaches 8.21 NTU, exceeding the allowable limit of 5 NTU. These results demonstrate that the system can effectively detect changes in water quality and provide early warnings through the dashboard and Telegram notifications.