ABSTRACT
Recent work has examined infrastructure-mediated sensing as a practical, low-cost, and unobtrusive approach to sensing human activity in the physical world. This approach is based on the idea that human activities (e.g., running a dishwasher, turning on a reading light, or walking through a doorway) can be sensed by their manifestations in an environment's existing infrastructures (e.g., a home's water, electrical, and HVAC infrastructures). This paper presents HydroSense, a low-cost and easily-installed single-point sensor of pressure within a home's water infrastructure. HydroSense supports both identification of activity at individual water fixtures within a home (e.g., a particular toilet, a kitchen sink, a particular shower) as well as estimation of the amount of water being used at each fixture. We evaluate our approach using data collected in ten homes. Our algorithms successfully identify fixture events with 97.9% aggregate accuracy and can estimate water usage with error rates that are comparable to empirical studies of traditional utility-supplied water meters. Our results both validate our approach and provide a basis for future improvements.
- Arregui, F.J., Palau, C.V., Gascon, L. and Peris, O. (2003). Evaluation of Domestic Water Meter Accuracy: A Case Study. E. Cabrera and E. Cabrera, eds. 343--352.Google Scholar
- Bao, L. and Intille, S.S. (2004). Activity Recognition from User-Annotated Acceleration Data. Proceedings of the International Conference on Pervasive Computing (Pervasive 2004), 1--17.Google ScholarCross Ref
- Beckmann, C., Consolvo, S. and LaMarca, A. (2004). Some Assembly Required: Supporting End-User Sensor Installation in Domestic Ubiquitous Computing Environments. Proceedings of the International Conference on Ubiquitous Computing (UbiComp 2004), 107--124.Google ScholarCross Ref
- Brumitt, B., Meyers, B., Krumm, J., Kern, A. and Shafer, S. (2000). EasyLiving: Technologies for Intelligent Environments. Proceedings of the International Symposium on Handheld and Ubiquitous Computing (HUC 2000), 12--29. Google ScholarDigital Library
- Chen, J., Kam, A.H., Zhang, J., Liu, N. and Shue, L. (2005). Bathroom Activity Monitoring Based on Sound. Proceedings of the International Conference on Pervasive Computing (Pervasive 2005), 47--61. Google ScholarDigital Library
- Evans, R., Blotter, J. and Stephens, A. (2004). Flow Rate Measurements Using Flow-Induced Pipe Vibration. Journal of Fluids Engineering 126(2). 280--285.Google ScholarCross Ref
- Fogarty, J., Au, C. and Hudson, S.E. (2006). Sensing from the Basement: A Feasibility Study of Unobtrusive and Low-Cost Home Activity Recognition. Proceedings of the ACM Symposium on User Interface Software and Technology (UIST 2006), 91--100. Google ScholarDigital Library
- Hirsch, T., Forlizzi, J., Hyder, E., Goetz, J., Kurtz, C. and Stroback, J. (2000). The ELDer Project: Social and Emotional Factors in the Design of Eldercare Technologies. Proceedings of the ACM Conference on Universal Usability (CUU 2000), 72--29. Google ScholarDigital Library
- Kim, Y., Schmid, T., Charbiwala, Z.M., Friedman, J. and Srivastava, M.B. (2008). NAWMS: Non-Intrusive Autonomous Water Monitoring System. Proceedings of the ACM Conference on Embedded Network Sensor Systems (SenSys 2008), 309--322. Google ScholarDigital Library
- Lester, J., Choudhury, T., Kern, N., Borriello, G. and Hannaford, B. (2005). A Hybrid Discriminative/Generative Approach for Modeling Human Activities. International Joint Conference on Artificial Intelligence (IJCAI 2005), 766--772. Google ScholarDigital Library
- Munguia Tapia, E., Intille, S.S. and Larson, K. (2004). Activity Recognition in the Home Using Simple and Ubiquitous Sensors. Proceedings of the International Conference on Pervasive Computing (Pervasive 2004), 158--175.Google Scholar
- Munguia Tapia, E., Intille, S.S., Lopez, L. and Larson, K. (2006). The Design of a Portable Kit of Wireless Sensors for Naturalistic Data Collection. Proceedings of the International Conference on Pervasive Computing (Pervasive 2006), 117--134. Google ScholarDigital Library
- Oppenheim, A. and Schafer, R. (2004). From Frequency to Quefrency: A History of the Cepstrum. IEEE Signal Processing Magazine 21(5). 95--106.Google ScholarCross Ref
- Patel, S.N., Reynolds, M.S. and Abowd, G.D. (2008). Detecting Human Movement by Differential Air Pressure Sensing in HVAC System Ductwork: An Exploration in Infrastructure Mediated Sensing. Proceedings of the International Conference on Pervasive Computing (Pervasive 2008), 1--18. Google ScholarDigital Library
- Patel, S.N., Robertson, T., Kientz, J.A., Reynolds, M.S. and Abowd, G.D. (2007). At the Flick of a Switch: Detecting and Classifying Unique Electrical Events on the Residential Power Line. Proceedings of the International Conference on Ubiquitous Computing (UbiComp 2007), 271--288. Google ScholarDigital Library
- Patel, S.N., Stuntebeck, E.P. and Robertson, T. (2009). PL-Tags: Detecting Batteryless Tags through the Power Lines in a Building. Proceedings of the International Conference on Pervasive Computing (Pervasive 2009), 256--273. Google ScholarDigital Library
- Patel, S.N., Truong, K.N. and Abowd, G.D. (2006). PowerLine Positioning: A Practical Sub-Room-Level Indoor Location System for Domestic Use. Proceedings of the International Conference on Ubiquitous Computing (UbiComp 2006), 441--458. Google ScholarDigital Library
- Philipose, M., Fishkin, K.P., Perkowitz, M., Patterson, D.J., Fox, D., Kautz, H. and Hahnel, D. (2004). Inferring Activities from Interactions with Objects. IEEE Pervasive Computing, 3(4). 50--57. Google ScholarDigital Library
- Rowan, J. and Mynatt, E.D. (2005). Digital Family Portrait Field Trial: Support for Aging in Place. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2005), 512--530. Google ScholarDigital Library
- Stuntebeck, E.P., Patel, S.N., Robertson, T., Reynolds, M.S. and Abowd, G.D. (2008). Wideband Powerline Positioning for Indoor Localization. Proceedings of the International Conference on Ubiquitous Computing (UbiComp 2008), 94--103. Google ScholarDigital Library
- Wilson, D. and Atkeson, C.G. (2005). Simultaneous Tracking&Activity Recognition (STAR) Using Many Anonymous, Binary Sensors. Proceedings of the International Conference on Pervasive Computing (Pervasive 2005), 62--79. Google ScholarDigital Library
Index Terms
- HydroSense: infrastructure-mediated single-point sensing of whole-home water activity
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