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Supporting data for "A low-cost, open source monitoring system for collecting high-resolution water use data on magnetically-driven residential water meters"
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| Type: | Resource | |
| Storage: | The size of this resource is 103.8 MB | |
| Created: | May 15, 2020 at 9:27 p.m. | |
| Last updated: | Jul 09, 2020 at 5:21 p.m. | |
| DOI: | 10.4211/hs.4de42db6485f47b290bd9e17b017bb51 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 2092 |
| Downloads: | 214 |
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Abstract
The files provided here are the supporting data and code files for the analyses presented in "A low-cost, open source monitoring system for collecting high-resolution water use data on magnetically-driven residential water meters," an article in Sensors (https://doi.org/10.3390/s20133655) The data included in this resource were collected in laboratory testing and field deployment of the Cyberinfrastructure for Intelligent Water Supply (CIWS) datalogger, an open source, low cost device capable of collecting high temporal resolution data on magnetically driven water meters. The code included allows replication of the analyses presented in the article, and the raw data included allow for extension of the analyses conducted. In the article we present a low-cost (≈ $150) monitoring system for collecting high resolution residential water use data without disrupting the operation of commonly available water meters. This system was designed for installation on top of analog, magnetically-driven, positive displacement, residential water meters and can collect data at variable time resolution intervals. The system couples an Arduino Pro microcontroller board, a datalogging shield customized for this specific application, and a magnetometer sensor. The system was developed and calibrated at the Utah Water Research Laboratory and was deployed for testing on five single family residences in Logan and Providence, Utah for a period of over 1 month. Battery life for the device was estimated to be over 5 weeks with continuous data collection at a 4 second time interval. Data collected using this system, under ideal installation conditions, was within 2% of the volume recorded by the register of the meter on which they were installed. Results from field deployments are presented to demonstrate the accuracy, functionality, and applicability of the system. Results indicate the device is capable of collecting data at a resolution sufficient for identifying individual water use events and analyzing water use at coarser temporal resolutions. This system is of special interest for water end-use studies, future projections of residential water use, water infrastructure design, and for advancing our understanding of water use timing and behavior. The system’s hardware design and software are open source, are available for potential reuse, and can be customized for specific research needs.
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Content
readme.md
Data and Code
The anonymized raw data collected and R code used to create the figures and tables included in the manuscript are available in this HydroShare product.
Folders are organized as follows:
- RawDataSample contains a sample of the magnetic field raw data (RawDataSample.CSV) measured on a water meter and the R script (RawData_figure1.R) used to generate Figure 1 in the manuscript.
- ValidationExperiment contains data from Experiments 1 and 2 described in the manuscript. Meter readings and the recorded pulses are available. Exp1 and Exp2 contain csv files with data for the 1 inch and the 5/8 inch meters. Figure6_LabExp.R contains code to generate Figure 6 in the manuscript, and Table7_LabExp.R has the code used to generate Table 7 in the manuscript.
- LabeledEvents contains a log with the events labeled at one of the sites (site1_ev.xlsx) where a CIWS datalogger was installed and the high temporal resolution data (001_0004.CSV) collected during the same period of time. LabeledEvents_Vis.R generates each panel in Figure 9 in the manuscript.
- FieldCampaign contains all the data collected in the field deployment conducted to test the functioning of the CIWS datalogger. meter_readings.xlsx contains the manual meter readings made at each field visit to the sites. The csv files (site1.csv, site2.csv...) contain the data collected for each site. Table 8 in the manuscript lists the data collection period at each site. PercentError_EDA.R generates Figure 8 in the manuscript. Events_RawData.R conducts event disaggregation and reproduces Figures 10 and 11, and table 10 in the manuscript.
All personally identifiable information was removed from the files published here to protect the identities of the study participants.
Instructions for Reproducing Results
To reproduce any of the results presented in the article, do the following: 1. Download the complete folders. Leave the files together in the folders to ensure the paths to the files remain correct. 2. Open the R scripts (https://cran.r-project.org/) using R or R-Studio (https://rstudio.com/) and execute them.
The code provided in this resource was developed using R version 4.0.0. The following R packages are required for running the provided scripts:
- egg - Version 0.4.5. Miscellaneous functions to help customize 'ggplot2' objects.
- lubridate - Version 1.7.8. Functions for working with dates/times.
- readxl - Version 1.3.1. A library for reading data from and writing data to Excel files.
- tidyverse - Version 1.3.0. A collection of R packages designed for data science.
- viridis - Version 0.5.1. A library that provides color maps for R.
- xts - Version 0.12-0. A library that provides uniform handling of R's time-based data classes.
Related Resources
| This resource is referenced by | Bastidas Pacheco, C.J., Horsburgh, J.S., Tracy, R.J. (2020). A low-cost, open source monitoring system for collecting high-resolution water use data on magnetically-driven residential water meters, Sensors, 20(13), 3655, https://doi.org/10.3390/s20133655. |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation | Cyberinfrastructure for Intelligent Water Supply (CIWS): Shrinking Big Data for Sustainable Urban Water | 1552444 |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
| Name | Organization | Address | Phone | Author Identifiers |
|---|---|---|---|---|
| Nour Atallah | Utah State University | Utah Water Research Laboratory, 8200 Old Main Hill, Logan, UT 84322 | ||
| Josh R Tracy | Utah State University | Utah Water Research Laboratory, 8200 Old Main Hill, Logan, UT 84322 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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