Abstract
This paper presents GasSense, a low-cost, single-point sensing solution for automatically identifying gas use down to its source (e.g., water heater, furnace, fireplace). This work adds a complementary sensing solution to the growing body of work in infrastructure-mediated sensing. GasSense analyzes the acoustic response of a home’s government mandated gas regulator, which provides the unique capability of sensing both the individual appliance at which gas is currently being consumed as well as an estimate of the amount of gas flow. Our approach provides a number of appealing features including the ability to be easily and safely installed without the need of a professional. We deployed our solution in nine different homes and initial results show that GasSense has an average accuracy of 95.2% in identifying individual appliance usage.
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References
Ao, X., Matson, J., Kucmas, P., Khrakovsky, O., Li, X.: UltraSonic Clamp-On Flow Measurement of Natural Gas, Steam, and Compressed Air, http://www.gesensing.com/products/resources/whitepapers/ur268.pdf (last accessed 10/16/2009)
Arroyo, E., Bonanni, L., Selker, T.: Waterbot: exploring feedback and persuasive techniques at the sink. In: CHI 2005, pp. 631–639. ACM, New York (2005)
Balasch, P.: National Gas and Electricity Costs and Impacts on Industry. National Energy Technology Laboratory, prepared for US Dept. of Energy, DOE/NETL-2008/1320 (2008)
Beckmann, C., Consolvo, S., LaMarca, A.: Some Assembly Required: Supporting End-User Sensor Installation in Domestic Ubiquitous Computing Environments. In: Davies, N., Mynatt, E.D., Siio, I. (eds.) UbiComp 2004. LNCS, vol. 3205, pp. 107–124. Springer, Heidelberg (2004)
Captor In-line Type Flow Meter, http://www.captor.com/ (last accessed 10/16/2009)
Chen, J., Kam, A.H., Zhang, J., Liu, N., Shue, L.: Bathroom Activity Monitoring Based on Sound. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 47–61. Springer, Heidelberg (2005)
Chicagoland Natural Gas Savings Program, http://www.conservationrebates.com/programs/chi/CHI_Index.aspx (last accessed on 10/16/2009)
Fischer, C.: Feedback on household electricity consumption: a tool for saving energy? Energy Efficiency 1, 79–104 (2008)
Flanagan, J.: Speech analysis synthesis and perception. Springer, New York (1972)
Fogarty, J., Au, C., Hudson, S.E.: Sensing from the Basement: A Feasibility Study of Unobtrusive and Low-Cost Home Activity Recognition. In: UIST 2006, pp. 91–100 (2006)
Froehlich, J., Findlater, L., Landay, J.: The Design of Eco-Feedback Technology. In: CHI 2010 (to appear 2010)
Froehlich, J., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., Patel, S.N.: HydroSense: infrastructure-mediated single-point sensing of whole-home water activity. In: UbiComp 2009, pp. 235–244 (2009)
Hirsch, T., Forlizzi, J., Hyder, E., Goetz, J., Kurtz, C., Stroback, J.: The ELDer Project: Social and Emotional Factors in the Design of Eldercare Technologies. In: Conference on Universal Usability, CUU 2000, pp. 29–72. ACM, New York (2000)
Kempton, W., Layne, L.: The Consumer’s Energy Analysis Environment. Energy Policy 22(10), 857–866 (1994)
Kim, Y., Schmid, T., Charbiwala, Z.M., Friedman, J., Srivastava, M.B.: NAWMS: Non-Intrusive Autonomous Water Monitoring System. In: Conference on Embedded Network Sensor Systems, SenSys 2008, pp. 309–322. ACM, New York (2008)
Kim, Y., Schmid, T., Charbiwala, Z., Srivastava, M.B.: ViridiScope: design and implementation of a fine grained power monitoring system for homes. In: UbiComp 2009, pp. 245–254 (2009)
Natural Gas Conservation and Ratemaking Efficiency Act § 56-600 et seq. Virginia (2009)
Patel, S.N., Robertson, T., Kientz, J.A., Reynolds, M.S., Abowd, G.D.: At the Flick of a Switch: Detecting and Classifying Unique Electrical Events on the Residential Power Line. In: Krumm, J., Abowd, G.D., Seneviratne, A., Strang, T. (eds.) UbiComp 2007. LNCS, vol. 4717, pp. 271–288. Springer, Heidelberg (2007)
US Energy Information Administration, Using and Saving Energy in Homes, http://tonto.eia.doe.gov/kids/energy.cfm?page=us_energy_homes (last accessed 10/16/2009)
Wilson, D., Atkeson, C.G.: STAR: Simultaneous Tracking & Activity Recognition Using Many Anonymous Binary Sensors. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 62–79. Springer, Heidelberg (2005)
Witten, I., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
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Cohn, G., Gupta, S., Froehlich, J., Larson, E., Patel, S.N. (2010). GasSense: Appliance-Level, Single-Point Sensing of Gas Activity in the Home. In: Floréen, P., Krüger, A., Spasojevic, M. (eds) Pervasive Computing. Pervasive 2010. Lecture Notes in Computer Science, vol 6030. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12654-3_16
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DOI: https://doi.org/10.1007/978-3-642-12654-3_16
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