Dissertation defense (December 16, 2022): Luis Barbosa de Assis Jr.

Student: Luis Barbosa de Assis Jr.

Title: An Internet of Things-based System for Water Leakage Detection in Households

Advisors: Diego Brandão e Helga Balbi

Committee: Diego Brandão (CEFET/RJ), Helga Balbi (CEFET/RJ), Felipe Henriques (CEFET/RJ), André Chaves (IME/IPB), Ary de Oliveira (UFT)

Day/Time: December 16, 2022 / 10a.m.

Room:https://teams.microsoft.com/l/meetup-join/19%3ameeting_Y2U5ZmY5NDUtOTg3OS00NDNhLWIxMWEtNTgwNTY2NjY5YzE2%40thread.v2/0?context=%7b%22Tid%22%3a%228eeca404-a47d-4555-a2d4-0f3619041c9c%22%2c%22Oid%22%3a%22b1b7c333-2713-4523-9eae-7d94d8adcbe5%22%7d

Abstract: The rational use of water is essential for a society’s development and economic growth. Data from the United Nations (UN) indicate that by 2050 there will be greater water scarcity due to the increase in demand in emerging countries, mainly with the population increase of these places (UN, 2018). A conscious consumption by society can mitigate such effects with the preservation of natural reserves and increased water security. This premise motivates the development of this work, which proposes creating a low-cost computer system that detects water leaks in residences using Internet of Things (IoT) concepts. This system includes data capture through sensing, transmission, processing, and a user interface. A hybrid edge and fog processing architecture was explored, as well as the leak detection techniques existing in the literature Consume Non-Zero and Minimum Night Flow. In addition, we present some contributions to leak detection and consumption analysis using Brazilian statistical data. We studied the impact of consumption and leakage on the internal pressure of the residence, and we presented the application of a machine learning algorithm to predict future consumption.