NAWMS: nonintrusive autonomous water monitoring system

ABSTRACT

Water is nature's most precious resource and growing demand is pushing fresh water supplies to the brink of non-renewability. New technological and social initiatives that enhance conservation and reduce waste are needed. Providing consumers with fine-grained real-time information has yielded benefits in conservation of power and gasoline. Extending this philosophy to water conservation, we introduce a novel water monitoring system, NAWMS, that similarly empowers users.

The goal of our work is to furnish users with an easy-to-install self-calibrating system that provides information on when, where, and how much water they are using. The system uses wireless vibration sensors attached to pipes and, thus, neither plumbing nor special expertise is necessary for its installation. By implementing a non-intrusive, autonomous, and adaptive system using commodity hardware, we believe it is cost-effective and widely deployable.

NAWMS makes use of the existing household water flow meter, which is considered accurate, but lacks spatial granularity, and adds vibration sensors on individual water pipes to estimate the water flow to each individual outlet. Compensating for manufacturing, installation, and material variabilities requires calibration of these low cost sensors to achieve a reasonable level of accuracy. We have devised an adaptive auto-calibration procedure, which attempts to solve a two phase linear programming and mixed linear geometric programming problem.

We show through experiments on a three pipe testbed that such a system is indeed feasible and adapts well to minimize error in the water usage estimate. We report an accuracy, over likely domestic flow-rate scenarios, with long-term stability and a mean absolute error of 7%.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS

General Terms:
Algorithms, Design, Experimentation, Human Factors, Measurement, Performance, Theory

Keywords:
adaptive sensor calibration, machine learning, nonintrusive and spatially distributed sensing, parameter estimation via optimization, tiered information architecture, water flow rate estimation