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HydroSense: infrastructure-mediated single-point sensing of whole-home water activity

Published: 30 September 2009 Publication History

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.

References

[1]
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.
[2]
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.
[3]
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.
[4]
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.
[5]
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.
[6]
Evans, R., Blotter, J. and Stephens, A. (2004). Flow Rate Measurements Using Flow-Induced Pipe Vibration. Journal of Fluids Engineering 126(2). 280--285.
[7]
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.
[8]
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.
[9]
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.
[10]
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.
[11]
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.
[12]
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.
[13]
Oppenheim, A. and Schafer, R. (2004). From Frequency to Quefrency: A History of the Cepstrum. IEEE Signal Processing Magazine 21(5). 95--106.
[14]
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.
[15]
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.
[16]
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.
[17]
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.
[18]
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.
[19]
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.
[20]
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.
[21]
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.

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    cover image ACM Conferences
    UbiComp '09: Proceedings of the 11th international conference on Ubiquitous computing
    September 2009
    292 pages
    ISBN:9781605584317
    DOI:10.1145/1620545
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 30 September 2009

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    Author Tags

    1. activity sensing
    2. infrastructure-mediated sensing
    3. water sensing

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    Ubicomp '09
    Ubicomp '09: The 11th International Conference on Ubiquitous Computing
    September 30 - October 3, 2009
    Florida, Orlando, USA

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    UbiComp '09 Paper Acceptance Rate 31 of 251 submissions, 12%;
    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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    • (2024)Monitoring domestic water consumption: a comparative study of model-based and data-driven end-use disaggregation methodsJournal of Hydroinformatics10.2166/hydro.2024.12026:4(709-726)Online publication date: 18-Mar-2024
    • (2024)Transforming Everyday Objects into IoT Control Interfaces: Design and Evaluation of the 'e-Rings' SystemArchives of Design Research10.15187/adr.2024.11.37.5.2937:5(29-49)Online publication date: 30-Nov-2024
    • (2024)ActSonic: Recognizing Everyday Activities from Inaudible Acoustic Wave Around the BodyProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997528:4(1-32)Online publication date: 21-Nov-2024
    • (2024)Human I/O: Towards a Unified Approach to Detecting Situational ImpairmentsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642065(1-18)Online publication date: 11-May-2024
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    • (2024)Data-Driven Wireless Fire Hose Flow Rate ApparatusIntelligent Building Fire Safety and Smart Firefighting10.1007/978-3-031-48161-1_17(415-438)Online publication date: 26-Jan-2024
    • (2023)PressureML: Modelling Pressure Waves to Generate Large-Scale Water-Usage Insights in BuildingsProceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3600100.3626636(463-467)Online publication date: 15-Nov-2023
    • (2023)waterFSA: A Contact-Less Water Flow Source Analyzer for the Household to Enable HAR and ADL Recognition2023 IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)10.1109/WETICE57085.2023.10477819(1-6)Online publication date: 14-Dec-2023
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