Supporting data and tools for "An Open-source, Semi-supervised Water End Use Disaggregation and Classification Tool"

The files provided here are the supporting data and code files for the analyses presented in "An Open-source, Semi-supervised Water End Use Disaggregation and Classification
Tool" a manuscript submitted to the Journal of Water Resource Planning and Management. The data included in this resource were collected using the CIWS-Logger (https://github.com/UCHIC/CIWS-WM-Logger) data logging device. Cyberinfrastructure for Intelligent Water Supply (CIWS) is an open-source, modular, generalized architecture designed to automate the process from data collection to analysis and presentation of high temporal residential water use data. The CIWS-Logger is a low cost device capable of collecting this type of data on existing, magnetically driven water meters. The code included in this resource (CIWS-Disaggregator) demonstrates a new water end use disaggregation and classification tool that builds on existing end use disaggregation studies and addresses the unavailability of code and data used by prior studies. The tool was developed in Python and can be accessed via any current Python programming environment. It was tested on anonymized, high temporal resolution datasets for five homes selected from a larger dataset for 31 homes located in the Cities of Logan and Providence Utah, USA. Results from different meter types and sizes are presented to demonstrate the accuracy of the tool in disaggregating and classifying high temporal resolution data into individual end use events. The results of this paper are reproducible using openly available code and data, representing an accessible platform for advancing end use disaggregation tools. The tool can be adapted to specific research needs.