Identifying household water use through transient signal classification

The research reported in this paper aims to develop a household water use identification method through signal pattern analysis. An experimental facility was constructed to simulate bathroom and kitchen water use. The data acquisition system used a volumetric water meter with pulsed output, pressure transducers, data acquisition with a Universal Serial Bus interface interconnected with the Cyble sensor and a laptop computer. The data analysis was performed using a pattern recognition algorithm to identify the hydraulic fixtures in use. Five classes of water use were considered, as follows: (1) kitchen faucet (KF), (2) washbasin faucet (WF), (3) bidet (BD), (4) shower (SH), and (5) toilet flush (TF). Two algorithms were used to identify the best classifier for the data, as follows: (1) multilayer perceptron, and (2) support vector machine (SVM). The fusion by majority vote regarding the results of SVM in the time domain showed the best accuracy; 92% accuracy for kitchen faucet, 94% for washbasin faucet, 94% for bidet, 100% for the shower, and 100% for toilet flush, thus supporting the use of signal signatures of flow and pressure in identifying the hydraulic fixtures in use.Foundation for Science and Technology (FCT) and Programa Operacional Potencial Humano and Fundo Social Europeu (POPH/FSE) under Ph.D. Grant SFRH/BD/66277/200

A preliminary investigation of water usage behavior in single-family homes

As regional drought conditions continue deteriorating around the world, residential water use has been brought into the built environment spotlight. Nevertheless, the understanding of water use behavior in residential buildings is still limited. This paper presents data analytics and results from monitoring data of daily water use (DWU) in 50 single-family homes in Texas, USA. The results show the typical frequency distribution curve of the DWU per household and indicate personal income, education level and energy use of appliances all have statistically significant effects on the DWU per capita. Analysis of the water-intensive use demonstrates the residents tend to use more water in post-vacation days. These results help generate awareness of water use behavior in homes. Ultimately, this research could support policy makers to establish a water use baseline and inform water conservation programs