Abstract: Water uses is increasing day by day. As development continues, the demand for water is increasing. Water is require for daily routine, for irrigation, for fish and wildlife and for industrial use, not only water but pure water is require. This is a helpful approach to make people or authorities aware and alert about water quality in real-time situation. In this paper, the proposed technology helps to monitor the water quality in real time situation or environment. The technology such as Internet of Things, Wireless Sensor Networkand Cloud Computingare used in this approach for water quality parameters (pH, minerals and Temperature) measuring in real-time environment. For water quality prediction and analysis, a training data set has been prepared and these training data sets use for categorize utility of water in different field. The sensor sensed the water parameters and send this sensed value to the cloud server for processing. These data compared with training data set. In this paper monitor data classify by using Naive Bayes and the utility of water can be predicted by Recurrent Neural Network. The resultant of this proposed approach are: it gives high accuracy and the response time of this approach is very less comparatively.