Research Article Open Access

A Study on Finding the Contamination Level in Water for Domestic Applications

Abstract

Management and control of Water is a Complex multi-disciplinary task requiring the adequate approaches and techniques. Traditional modeling of physical process is often tries to explain the underlying processes. On this the so called Data-driven technique, borrowing heavily from artificial intelligence techniques, are based on limited knowledge of modeling process and relay on data describing the input and output characteristics. In this project application of widely used particular types of data driven models, namely artificial neural network(ANN) is used to model the water resource management field. Neural network has been successfully applied to wide range of problems covering the variety of sectors. During this ANN evolved from being only a research tool that is applied to many real world problems. Sensors play a vital role in detecting the impurities in water. However, in this project a wide range of wireless sensors are being operated in the water field, to detect the contamination level. In this project sensors namely PH, TURBIDITY, CONDUCTIVITY, HARDNESS and CALCIUM detection sensors are being employed.

Srinivas.S, Dr .P.M Murali, B.Rajasekaran, D .Padmarajan

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