Nour Attallah

Utah State University

Subject Areas: Water Management, Hydro-informatics

 Recent Activity

ABSTRACT:

The files provided here are the supporting data and code files for the analyses presented in "Residential Water Meters as Edge Computing Nodes: Disaggregating End Uses and Creating Actionable Information ath the Edge," an article submitted to the Sensors journal. The data included in this resource were collected in a field deployment of the Cyberinfrastructure for Intelligent Water Supply (CIWS) Computational Node, an open source, low cost device capable of collecting, processing, and transferring high temporal resolution data on magnetically driven water meters. The code included allows replication of the findings presented in Sections 4.3 and 4.4 of the article, and the raw and processed data included allow for extension of the analyses conducted.

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ABSTRACT:

The files provided here are the supporting data and code files for the analyses presented in "Tools for Evaluating, Developing, and Testing Water End Use Disaggregation Algorithms," 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.

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ABSTRACT:

This resource contains the final high frequency data files, R scripts, and the C# code used in our analysis of water use across 6 different non-residential facilities in the City of Logan, UT. We utilized the current Neptune water meters the City has. We replaced the meter heads (E-Coders) used for monthly billing purposes with new ones (Innov V8) that log at five minute intervals. We dialed down the reading frequency to five second intervals by deploying 101A data loggers. The data loggers are attached at each meter head through a 2-wire pulse cable. We placed the loggers inside weather-proof enclosures to protect them from moisture. Without the need for installing individual meters for every water end use, we identified different water use events, average water use per end use, variability in end uses (faucets/toilets versus showers), variability in use by the type of user (manufacturing versus assisted care facilities) and the potential signature of different fixtures. We validated our findings with the feedback from participating businesses’ representatives where we inspected whether the results matched the expected water use behavior of the business. We applied the Gallons Per Capita Day (GPCD) method to investigate the water use behavior of non-residential users and compared it to residential users. We investigated the diurnal water use patterns and trends for the participants, where we found that users exhibited heterogeneous water use patterns. Finally, we recommend some conservation actions for the participants of this study. The findings from this research can help the water managers in Logan City with better understanding of commercial, industrial, and institutional (CII) water use behavior and an insight for future water supply planning for the CII sector.

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Composite Resource Composite Resource

ABSTRACT:

This resource contains the final high frequency data files, R scripts, and the C# code used in our analysis of water use across 6 different non-residential facilities in the City of Logan, UT. We utilized the current Neptune water meters the City has. We replaced the meter heads (E-Coders) used for monthly billing purposes with new ones (Innov V8) that log at five minute intervals. We dialed down the reading frequency to five second intervals by deploying 101A data loggers. The data loggers are attached at each meter head through a 2-wire pulse cable. We placed the loggers inside weather-proof enclosures to protect them from moisture. Without the need for installing individual meters for every water end use, we identified different water use events, average water use per end use, variability in end uses (faucets/toilets versus showers), variability in use by the type of user (manufacturing versus assisted care facilities) and the potential signature of different fixtures. We validated our findings with the feedback from participating businesses’ representatives where we inspected whether the results matched the expected water use behavior of the business. We applied the Gallons Per Capita Day (GPCD) method to investigate the water use behavior of non-residential users and compared it to residential users. We investigated the diurnal water use patterns and trends for the participants, where we found that users exhibited heterogeneous water use patterns. Finally, we recommend some conservation actions for the participants of this study. The findings from this research can help the water managers in Logan City with better understanding of commercial, industrial, and institutional (CII) water use behavior and an insight for future water supply planning for the CII sector.

Show More
Composite Resource Composite Resource

ABSTRACT:

The files provided here are the supporting data and code files for the analyses presented in "Tools for Evaluating, Developing, and Testing Water End Use Disaggregation Algorithms," 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.

Show More
Composite Resource Composite Resource

ABSTRACT:

The files provided here are the supporting data and code files for the analyses presented in "Residential Water Meters as Edge Computing Nodes: Disaggregating End Uses and Creating Actionable Information ath the Edge," an article submitted to the Sensors journal. The data included in this resource were collected in a field deployment of the Cyberinfrastructure for Intelligent Water Supply (CIWS) Computational Node, an open source, low cost device capable of collecting, processing, and transferring high temporal resolution data on magnetically driven water meters. The code included allows replication of the findings presented in Sections 4.3 and 4.4 of the article, and the raw and processed data included allow for extension of the analyses conducted.

Show More