Detection of Water Quality using Machine Learning and IoT

Abstract

Water is one of the most crucial elements for the existence of life. Drinking-water safety and accessibility are pressing issues all over the world. Drinking water which is polluted with contagious agents, harmful chemicals, and other contaminants may pose health concerns. In this work, a method for analyzing water quality and warning users when water becomes polluted is presented. Water can be contaminated by a variety of factors. These factors are taken into consideration and utilised to forecast whenever its time to clean the water. The system makes use of IoT and Machine Learning technology. It consists of physical and chemical sensors that detect pH, Turbid- ity, Color, Dissolved Oxygen, Conductivity to check influencing factors.The data collected by the sensors is saved in a database and then submitted for analysis. The neural network method is used to forecast the outcome. It is employed in order to generate a non-linear connection for projected output. When any of the parameters falls below the standard values, the system sends an alarm notification to the user. This enables the user to be aware of water pollution in their home tanks ahead of time. This technology is not restricted to home tanks; it may also be applied in water treatment facilities and enterprises.

Status - Published

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