Real Time Water Contamination Monitoring Using Digital Twin Approach

This Real-time monitoring of water quality is essential for protecting public health and ensuring safe water usage in domestic, industrial, and environmental applications. Conventional laboratory-based testing methods are often time-consuming, discontinuous, and unsuitable for instant contamination detection. To address these limitations, this work proposes a Real-Time Water Contamination Monitoring System Using a Digital Twin Approach. The system integrates a Raspberry Pi as the main processing unit with pH, turbidity, Total Dissolved Solids (TDS), and temperature sensors for continuous measurement of critical water quality parameters. A digital twin model is used to maintain synchronization between the physical monitoring unit and its virtual representation, enabling real-time analysis, status evaluation, and intelligent alert generation. In the proposed system, sensor data are acquired continuously and compared with predefined threshold values to determine whether the water condition is safe or abnormal. During experimental testing, the system successfully initialized with the LCD message “Data Reading Started” and continuously displayed live sensor outputs. Under normal conditions, the observed values were within acceptable ranges, approximately pH = 7.0–7.4, temperature = 27–30 °C, TDS = 280–420 ppm, and turbidity = 1.2–3.8 NTU, and the system classified the water as safe. When abnormal conditions were introduced, the parameters exceeded threshold limits such as pH 8.5, TDS > 500 ppm, turbidity > 5 NTU, and temperature > 35 °C, causing the LCD to display “Status: Abnormal”. The alert mechanism operated correctly during unsafe conditions. The red LED and buzzer were activated immediately, while safe water conditions were indicated through the green LED. In addition, the system generated an SMS notification with the message “Sending SMS Please Wait...”, confirming successful remote alert transmission to the user.