Embedded processor based automated assessment of quality of the water in an IoT background

Abstract

For the life of human beings, water is necessary. While nearly 70% of the earth is drained, just 3% are known to be fresh water. Moreover, approximately 2.6% of the cooling water is not accessible to people. They are either trapped in glaciers and polar ice caps, contained in the soil or water, heavily poisoned, or unnecessarily drained below the Earth's surface. So only 0.4% of the drinkable water in the world is shared by the 7 billion inhabitants. Fresh water is therefore a valuable resource to be regulated and properly maintained. Only 80% of liquid fresh water should not be available to the public in many developing countries. By exponentially increasing the population of India, Fresh Water management in the farming, manufacturing and other fields is much more critical because of water requirements. “Physical, biological and chemical” parameters can be analyzed in determining the Fresh Water Quality. The scientists will manually carry out traditional water quality sampling. Nonetheless, this method takes a little bit of time and is cost-effective. Now, the IoT technology is used to track, capture and analyze the data in various fields of research. In this paper, we design a low-cost system to achieve water value in an IOT environment. The system consists of several sensors used for the calculation of chemical and physical water parameters. The machine learning algorithm has also been used to forecast water quality based on its data set, which were learned from a number of water samples. This system was modeled by using the U D00* 86 Ultra and Teensy++2.0 data processors at low budgets.