Predicting the Quality of Treated Water from an Activated Carbon Based Water Purifier Using Artificial Neural Network

Abstract

Automated water purifier is a convenient and widely used device for obtaining purified water. However, performance of a system may vary over time and therefore monitoring of the treated water is essential for ensuring the quality control. In this study, a number of input and output samples of an activated carbon based water purifying system were monitored to check its efficiency. Overall quality of the inflow and outflow of the purifying system were assessed by Weighted Arithmetic Water Quality Index with ideal permissible limits of the water quality parameters as per Indian Council of Medical Research guidelines. Results indicate that the quality of the water enhanced significantly after purification. A model was developed from the water quality data with Artificial Neural Network to predict the quality of the water, treated by the purifier. The model was tested with more water quality data and found to be successful in prediction of the overall quality of the treated water fairly accurately.