In many industries once performed with people doing manual labor, today we have machines running these functions, Robots or just a computer system with enough information to analyze and process data deciding how best to apply them, these systems are so capable of molding to any reality that does not need to be operated by any person, but it needs a training with input of data for an already defined answer, this type of System is called RNA - Artificial Neural Network. In sanitation, one of the issues that most concerns is the critical way in which the water supply system is made for the population on a continuous basis, or it is a lot of supply due to low demand or too much demand for the supply. If it is to evaluate the moments of greatest consumption in the period of one day, it will be possible to verify moments of no consumption or very low consumption and also to take into account operational problems in several ways such as: lack of energy, accidents, lack of equipment maintenance among others. The sums of all these factors hinder supply, a way of predicting water consumption can help and minimize such problems in the system. In this sense, the present research has the objective of showing succinctly and objectively ways of how it is possible to apply autonomous means of management for sanitation management in water supply systems. With this new technology the errors can be minimized, allowing the improvement in several procedures that are still flawed, allowing agility and efficiency in the water supply processes. With the use of autonomous systems for data collection and storage, through automated supervisory and control systems (SCADA), the water consumption forecast can be made in more detail and in time intervals such as hours, minutes and seconds.
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