Sound recording to characterize outdoor tap water use events

Obtaining disaggregated water use at the home typically involves expensive smart metering. In this study, water use events at the outdoor tap were alternatively captured using recorded sound. Outdoor taps at 10 homes were fitted with small-sized microphones and digital sound recorders. Sound files recorded over a one-month period were used in the analysis. In the preliminary analysis, a human operator browsed through the sound recordings, picking out tap use events based on visually recognizable waveform and spectrogram features, then audibly verifying each event identified before labeling. The performance of the corresponding automatic detection algorithm was reasonable, showing that water use events can be detected at precision and recall rates of at least 80% under suitable conditions. The results also showed that the technique is less suitable where the drop in pressure during peak demand periods results in significant reduction in the tap flowrate. Indirect flow sensing approaches are attractive for investigating water use event timing, because of the relatively lower cost when compared to conventional or smart water meters. Plumbing changes are not required as the recorder can be mounted on any exposed pipe section near the fixture of interest.

[1]  Eric C. Larson,et al.  HydroSense: infrastructure-mediated single-point sensing of whole-home water activity , 2009, UbiComp.

[2]  R. P. Evans,et al.  Flow Rate Measurements Using Flow-Induced Pipe Vibration , 2004 .

[3]  Yue Zhang LOW COST FLOW SENSING FOR FIELD SPRAYERS , 2014 .

[4]  Mani B. Srivastava,et al.  A longitudinal study of vibration-based water flow sensing , 2012, ACM Trans. Sens. Networks.

[5]  Yosuke Kurihara,et al.  Development of Vibration Sensor with Wide Frequency Range Based on Condenser Microphone -Estimation System for Flow Rate in Water Pipes- , 2012 .

[6]  Kemal Polat,et al.  A new feature selection method on classification of medical datasets: Kernel F-score feature selection , 2009, Expert Syst. Appl..

[7]  James Fogarty,et al.  Sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition , 2006, UIST.

[8]  John K. Stamer,et al.  Pesticide distributions in surface water , 1996 .

[9]  Theodoros Giannakopoulos,et al.  Introduction to audio analysis , 2016 .

[10]  P. Fearnhead,et al.  Analysis of changepoint models. , 2011 .

[11]  Ning Liu,et al.  Bathroom Activity Monitoring Based on Sound , 2005, Pervasive.

[12]  Peter W. Mayer,et al.  Flow trace analysis to access water use , 1996 .

[13]  Y Skibbe,et al.  13th Computer Control for Water Industry Conference, CCWI 2015 Correlating sound and flow rate at a tap , 2015 .

[14]  Arjun K. Gupta,et al.  Parametric Statistical Change Point Analysis , 2000 .