Soft Computing Framework for Assessment of Water Quality in Distribution Network

Modern techniques are replacing traditional methods of water quality parameter measurement systems. Continuous effective online monitoring with user friendly decision support system is one of the essential challenges of water quality monitoring system. To achieve the goal of development of user friendly decision support system for monitoring of potable water in distribution network, this paper introduces soft computing framework, mainly consist of Python programming framework and fuzzy sets. In so far, we have exploited the properties of NumPy and Matplotlib libraries of Python for user interface and fuzzy sets for decision support system. The proposed decision support system collects and utilizes the data points generated from integrated Multi Sensor Array and process the obtained data set through rule based fuzzy sets. Effective user interface and decision making are essential prerequisite of any decision support system. Therefore, we developed Rule Based Decision Support System (RBDSS) strategy to measure the extent of potability of water in distribution network. Based on extensive research, five water quality parameters has been considered to implement decision support system i.e pH, Dissolved Oxygen (D.O.), Electrical Conductivity (E.C.), Oxygen Reduction Potential (O.R.P) and Temperature. The conducted study to test the feasibility of proposed decision support system testify the plausibility of framework in water quality distribution network.