Studying the extent of rationalizing domestic water consumption using fuzzy logic

Abstract

During the last ten years, the population of Tripoli has increased significantly due to the recent events in the country, and this has placed a burden on the city's infrastructure, including the domestic water network. The is research aims to rationalize domestic water consumption by applying artificial intelligence programs to identify different consumption patterns using the smallest of maximum ( SOM )and the centroid of area (COA) methos, and thus determine the procedures that will limit domestic water consumption. To achieve this, a questionnaire was conducted and distributed to 170 consumers in the Abu Salim municipality, the subject of the research, during the winter period extending from January 2024 to March 2024. It consists of 45 indicators, and six indicators were chosen as the most influential from the researchers' point of view. In this research, the most comprehensive artificial intelligence tools, Fuzzy Logic, were used using the Mamdani model, by fuzzing the data obtained and analyzing them using MATLAB by linking household water consumption patterns to the extent of rationalizationof consumption, as the results of the two methods used indicated that rationalization was poor by 41% in the firstmethod, and average in the second method 55%, which is the extent of rationalization of household water consumption according to the model prepared by the researchers, and is considered a dangerous indicator due to the increasing water consumption in recent years. Thus, it was concluded from the research that there is some awareness of the importance of water consumption, and the research recommended that awareness of the importance of rationalizing water consumption must be increased through continuous media and awareness, so that the water of the Man-Made River and wells is for drinking and household consumption, and also the possibility of recycling household water to reuse it in garden irrigation and washing floors, especially recycling water consumed in kitchens.