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Hardware design and software for smart water metering using embedded computers.

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Cyberinfrastructure for Intelligent Water Supply (CIWS)

CIWS is a project funded by the U.S. National Science Foundation to develop cyberinfrastructure for smart water metering and high resolution water-use data collection. We are developing systems for high resolution residential water consumption data collection, processing and analysis.

As part of this project, we have developed three prototype data logging devices for collecting high-resolution water use data. These include:

  • CIWS-WMW-Logger - Smart water meter datalogger for magnetically-driven water meters
  • CIWS-EWM-Logger - Smart water meter datalogger for electronic output water meters
  • CIWS-WM-Node - Smart water meter computational node

All current development work on hardware and software related to these devices is ongoing in the GitHub repositories linked above. We are maintaining this repository for legacy/archive purposes only.

This repository contains legacy files and documentation for prior versions of the water use dataloggers we developed to support our smart water metering research at the Utah Water Research Laboratory at Utah State University. We are using low cost, commercially available, embedded computers and sensors to log data from existing analog residential water meters (magnetically-driven positive displacement meters) as well as commercial water meters with pulsed or current loop outputs (4-20 mA).

Using these devices, we are developing ways to turn most analog, positive displacement water meters with detachable registers into a smart water meter with capabilities to store high frequency flowrate data for up to weeks at a time on a single battery charge. We are also developing new cyberinfrastructure and techniques for collecting high frequency data from commercial water meters.

The following is an example of the type of data we are collecting from individual residences:

Data

Sponsors and Credits

NSF-1552444

This material is based on work supported by National Science Foundation Grant CBET 1552444. Any opinions, findings, and conclusions or recommendations expressed are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.