Smart Water Distribution System using Machine Learning and IoT

Abstract

Water Management includes four major processes, namely, estimating the amount of water readily available to be distributed, the measurement of the quality of water, distribution of water to different sectors of the city based on the quality and finally to provide a platform to monitor this distribution from anywhere and by anyone. All these processes, are currently treated as separate modules, but the integration of these four models, enhances water conservation and creates a social awareness since the proposed cloud platform can be accessed by everyone, and they are made aware, in advance, about the quality and amount of water they are going to get for the week, so that they can use the water wisely. In this paper we discuss our new and improved proposed model which not only integrates the existing four modules but also optimizes the distribution path based on algorithms for the fastest coverage. This is turn provides a short and concise solution to water management which is more user friendly and can reach more people, hence spreading more awareness. The lack of coordination between the current quality measurement and distribution system calls for an integrated system. This system predicts the rainfall to prepare the system for the amount of softener required to soften the water which acquires calcium and magnesium as it makes its way into other natural rivers. This water management system can be setup both on a small scale and a large scale. The smaller water management system setup in villages can be interconnected to make a larger water management system that can be centrally controlled from cities which helps in ensuring water distribution even in the smallest towns and villages.