Wireless Water Quality Monitoring and Quality Deterioration Prediction System

Abstract

Water is an essential resource in day-to-day life. Pollution and urbanization have led to higher susceptibility of source water to contamination. There is a pressing need to develop a water quality monitoring system to preserve the quality of source water and ultimately safeguard human health. This paper proposes a low cost, wireless water quality monitoring system, wherein the quality of water stored in overhead tanks is continuously monitored. The quality of water is measured by parameters that are critical quality indicators. The data encompassing these parameters are stored in a Cloud database (in real-time) along with its timestamp. The quality of water is ascertained based on the comparison of the monitored data to standard well-established thresholds. The data, annotated with its timestamp is treated as a time-series. A univariate non-seasonal AutoRegressive Integrated Moving Average (ARIMA) model is employed to forecast individual water quality parameters. The results of forecasting is used to predict water quality deterioration. The model used is found to have mean square errors of 0.001 for pH, 0.076 for temperature and 0.001 for turbidity between the actual and forecasted values.