A Proficient Prediction Mechanism for Analyzing Water Quality Using Machine Learning Algorithms

Water quality prediction includes the finding the level of contamination which helps further to develop the strategies to maintain the water quality. Health is wealth. To maintain good health, one should have non polluted drinking water which is becoming one of the major problems. The major challenge to the people knowing whether the water is potable or not. Also, based on the composition of the elements of water, the human health can be predicted. Of course, by knowing its level of composition of each element it will be easier to predict the water hazards. Both the public and the government will be benefited if they receive regular reports on the state of the water including element composition and their levels for all areas. If the people have water quality reports, then they can take the necessary precautions to avoid the health problems. The proposed research work has made an attempt to predict the water quality with the help of machine learning algorithms random forest, XGboost and SVM. Here, this study has achieved an improved accuracy when compared to the existing system and addition ally CNN and RCNN are applied to check the accuracy.