Performance Analysis of Water Quality Monitoring System in IoT Using Machine Learning Techniques

Nowadays, the Internet of things (IoT) and insights while sensing are being used in different areas of research to monitor, collect and separate knowledge from various sources of interest. As there is a huge increase in contamination of water from the industries in provincial to urban regions and over-use of land and ocean assets, the nature of water that each person can use has turned out to be more regrettable. High utilization of composts for crops and different synthetic concoctions in different segments like thermal and electrical power plants, leakages in the submarine pipeline, mining, and construction has significantly added to the general dip in water quality level as a whole. Water is the most significant need for human survival and thus there must be a framework made to test water characteristics and availability for drinking in urban communities and towns. The accessibility of good and better quality of water is most significant in counteracting outbreaks of waterborne diseases just as improving the quality of life. The point of the work proposed is to present a water quality observing system using machine learning techniques.