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The design and evaluation of prototype eco-feedback displays for fixture-level water usage data

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Published:05 May 2012Publication History

ABSTRACT

Few means currently exist for home occupants to learn about their water consumption: e.g., where water use occurs, whether such use is excessive and what steps can be taken to conserve. Emerging water sensing systems, however, can provide detailed usage data at the level of individual water fixtures (i.e., disaggregated usage data). In this paper, we perform formative evaluations of two sets of novel eco-feedback displays that take advantage of this disaggregated data. The first display set isolates and examines specific elements of an eco-feedback design space such as data and time granularity. Displays in the second set act as design probes to elicit reactions about competition, privacy, and integration into domestic space. The displays were evaluated via an online survey of 651 North American respondents and in-home, semi-structured interviews with 10 families (20 adults). Our findings are relevant not only to the design of future water eco-feedback systems but also for other types of consumption (e.g., electricity and gas).

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References

  1. Aitken C., McMahon, T., Wearing, A., et al. (1994). Residential Water Use: Predicting and Reducing Consumption. J.of Applied Social Psychology; 24 (2):136--158.Google ScholarGoogle Scholar
  2. Arroyo, E., Bonanni, L., & Selker, T. (2005). Waterbot: Exploring Feedback & Persuasive Techniques at the Sink. CHI'05, 631--639. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Corral-Verdugo, V., Bechtel, R., & Fraijo-Sing, B. (2003). Environmental Beliefs and Water Conservation: An Empirical Study. Journal of Environmental Psychology, 23(3).Google ScholarGoogle ScholarCross RefCross Ref
  4. Ehrhardt-Martinez, K., et al (2010). Advanced Metering Initiatives and Residential Feedback Programs: Meta-Review for Household Electricity-Saving Opportunities. ACEEE'10; 1--140.Google ScholarGoogle Scholar
  5. Feng Chen, Jing Dai, et al. (2011). Activity Analysis Based on Low Sample Rate Smart Meters. Proc. of KDD '11; 240--248. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Fischer, C. (2008) Feedback on Household Electricity Consumption: a Tool for Saving Energy? En. Efficiency; 1(1):79--104.Google ScholarGoogle Scholar
  7. Froehlich, J. (2011). Sensing and Feedback of Everyday Activities to Promote Environmental Behaviors. Doctoral dissertation. University of Washington, Seattle.Google ScholarGoogle Scholar
  8. Froehlich, J., Dillahunt, T., Klasnja, P., et al. (2009). UbiGreen: Investigating a Mobile Tool for Tracking and Supporting Green Transportation Habits. CHI'09, 1043--1052. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Froehlich J., Findlater L., & Landay J. (2010). The Design of EcoFeedback Technology. CHI'10, 1999--2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Froehlich, J., Larson, E., et al. (2011). Disaggregated End-Use Energy Sensing for the Smart Grid. Perv. Computing, 28--39. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Froehlich, J., Larson, E., Saba, E., et al. (2011). A Longitudinal Study of Pressure Sensing to Infer Real-World Water Usage Events in the Home. Pervasive'11; 50--69. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Gleick, P., Cooley, H., & Morikawa, M. (2008). The World's Water 2008-2009: Biennial Report on Freshwater Resources. Island Press.Google ScholarGoogle Scholar
  13. Glennon, R. (2009). Unquenchable: America's Water Crisis and What to Do about It. Island Press.Google ScholarGoogle Scholar
  14. Geller, E., Ericksson, J., & Buttram, B. (1983). Attempts to Promote Residential Water Conservation with Educational, Behavioral and Engineering Strategies. Population and Environment. 6(2):96--112.Google ScholarGoogle ScholarCross RefCross Ref
  15. Hamilton, L. (1983). Saving Water: A Causal Model of Household Conservation. Sociological Perspectives. 26(4); 355--374.Google ScholarGoogle Scholar
  16. Hruschka, D., Schwartz, D., et al. (2004). Reliability in Coding Open-Ended Data: Lessons Learned from HIV Behavioral Research. J. of Field Methods. 16(3): 307--331.Google ScholarGoogle ScholarCross RefCross Ref
  17. Inman, D., & Jeffrey, P. (2006). A Review of Residential Water Conservation Tool Performance and Influences on Implementation Effectiveness. Urban Water J., 3(3):127--143.Google ScholarGoogle ScholarCross RefCross Ref
  18. Kantola, S., Syme, G., & Nesdale, A. (1983). The Effects of Appraised Severity and Efficacy in Promoting Water Conservation: An Informational Analysis. J. Applied Social Psych. 13(2):164--182.Google ScholarGoogle ScholarCross RefCross Ref
  19. Kappel K, & Grechenig, T. (2009). "show-me": Water Consumption at a Glance to Promote Water Conservation in the Shower. Persuasive'09. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Kenney, D., Goemans, C., Klein, R., et. al.(2008). Residential Water Demand Management: Lessons from Aurora, Colorado. J. of American Water Resources Association; 44(1), 192--207.Google ScholarGoogle Scholar
  21. Kuznetsov, S., & Paulos, E. (2010). UpStream: Motivating Water Conservation with Low-Cost Water Flow Sensing and Persuasive Displays. CHI'10, 1851--1860. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Laschke, M., et al. (2011). With a Little Help from a Friend: A Shower Calendar to Save Water. CHI'11 Extended Abstracts. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Laskey & Kavazovic. (2011). OPOWER. XRDS 17(4); 47--51. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Mayer, P., DeOreo W., Opitz E., et al. (1999). Residential End Uses of Water. AWWA Research Foundation.Google ScholarGoogle Scholar
  25. Riche, Y., Dodge, J., & Metoyer R, (2010). Studying Always-On Electricity Feedback in the Home. Proc of CHI '10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Rodgers, J. & Bartram, L. Visualizing Residential Resource Use: A Framework for Design. Proc. of InfoVis 2010. Poster.Google ScholarGoogle Scholar
  27. Strengers, Y. (2008). Smart Metering Demand Management Programs: Challenging the Comfort and Cleanliness Habitus of Households. OZCHI'08, 9--16. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. US Department of Energy, US Household Electricity Report, Energy Information Administration, US DOE, 2001.Google ScholarGoogle Scholar
  29. Vickers A. (2001). Handbook of Water Use and Conservation: Homes, Landscapes, Industries, Businesses. WaterPlow Press.Google ScholarGoogle Scholar
  30. Willis, R., et. al. (2010). Alarming Visual Display Monitors Affecting Shower End Use Water and Energy Conservation in Australian Residential Households. Resources, Conservation and Recycling. 54(12):1117--1127.Google ScholarGoogle ScholarCross RefCross Ref

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  1. The design and evaluation of prototype eco-feedback displays for fixture-level water usage data

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      cover image ACM Conferences
      CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
      May 2012
      3276 pages
      ISBN:9781450310154
      DOI:10.1145/2207676

      Copyright © 2012 ACM

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      Publication History

      • Published: 5 May 2012

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