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| Created: | Oct 19, 2022 at 8:18 p.m. | |
| Last updated: | Jul 06, 2023 at 7:23 p.m. | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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Abstract
This resource contains raw data collected for the project "Increasing the Water Conservation Impact of Utah State University’s (USU) Extension Water Check Program with 5 Second Metering" (https://uwrl.usu.edu/water-check-study) The data is for ~ 78 households in Logan and Hyde Park, Utah collected in Summer and Fall 2022. 5-second water use data was collected over the entire period using a Flume Smart Home Water Monitoring Device. After ~ two weeks, a USU Extension Water Check was conducted during a site visit. There are 6 data sets in this resource. Data are anonymized and can be linked -- joined -- by the SiteID field.
1_Database_CSVFiles/
1) FlumePropertyData.csv => Metadata for the households collected by Flume when a device is installed and the Flume phone App was installed.
2) Sites.csv => Metadata for the households including city, state, and zipcode.
3) WaterCheckData.csv => Parcel, landscape, and irrigation system data collected as part of the USU Extension Water Check during a 1-hour visit to the household. Data also include Water Check recommendations to reduce irrigation water use.
4) RawWaterUseData/SITE_XXX.csv => Raw 5-second water use data collected by Flume Smart Home Water Monitoring Devices (http:/FlumeWater.com). One file for each household/SiteID. XXX is the SiteID.
5) daily_WeatherData_GVFarm.csv => Weather data from the nearest station - Greenville Farm, Cache Valley, Utah.
6) TrainingData.csv => Irrigation events identified by duration (minutes), volume_gal (gallons), average_fr_GPM (gallons per minute), label (type of event). These data are used to train a model that uses the raw 5-second data to classify irrigation events.
The code to classify the raw 5-second water use data is in a separate code repository - https://github.com/cjbas22/HelpUSUExtensionP.
2_AdditionalData => Folder with duplicate copies of the weather station and training data.
3_Database => Empty folder. Code in the repository https://github.com/cjbas22/HelpUSUExtensionP reads the raw csv files and creates a database with tables for each data file.
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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