Advertisement

Detecting Human Movement by Differential Air Pressure Sensing in HVAC System Ductwork: An Exploration in Infrastructure Mediated Sensing

  • Shwetak N. Patel
  • Matthew S. Reynolds
  • Gregory D. Abowd
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5013)

Abstract

We have developed an approach for whole-house gross movement and room transition detection through sensing at only one point in the home. We consider this system to be one member of an important new class of human activity monitoring approaches based on what we call infrastructure mediated sensing, or "home bus snooping." Our solution leverages the existing ductwork infrastructure of central heating, ventilation, and air conditioning (HVAC) systems found in many homes. Disruptions in airflow, caused by human inter-room movement, result in static pressure changes in the HVAC air handler unit. This is particularly apparent for room-to-room transitions and door open/close events involving full or partial blockage of doorways and thresholds. We detect and record this pressure variation from sensors mounted on the air filter and classify where certain movement events are occurring in the house, such as an adult walking through a particular doorway or the opening and closing of a particular door. In contrast to more complex distributed sensing approaches for motion detection in the home, our method requires the installation of only a single sensing unit (i.e., an instrumented air filter) connected to an embedded or personal computer that performs the classification function. Preliminary results show we can classify unique transition events with up to 75-80% accuracy.

Keywords

Activity Recognition Motion Sensor Sensor Unit Differential Pressure Sensor Detect Human Movement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    ADT QuietCare (2008), http://www.adt.com/quietcare/
  2. 2.
    American Institute of Architects. Guidelines for Design and Construction of Hospital and Health Care Facilities. The American Institute of Architects Press, Washington D.C. (2001)Google Scholar
  3. 3.
    Barnes Reports. 2008 U.S. Plumbing & Heating & A/C Contractors Report (October 2007)Google Scholar
  4. 4.
    Bian, X., Abowd, G.D., Rehg, J.M.: Using Sound Source Localization in a Home Environment. In: Proc. of the Pervasive 2005, pp. 19–26 (2005)Google Scholar
  5. 5.
    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. 383–399. Springer, Heidelberg (2004)Google Scholar
  6. 6.
    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)CrossRefGoogle Scholar
  7. 7.
    Chetty, M., Sung, J., Grinter, R.E.: How Smart Homes Learn: The Evolution of the Networked Home and Household. In: Krumm, J., Abowd, G.D., Seneviratne, A., Strang, T. (eds.) UbiComp 2007. LNCS, vol. 4717, pp. 127–144. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Fogarty, J., Au, C., Hudson, S.E.: Sensing from the Basement: A Feasibility Study of Unobtrusive and Low-Cost Home Activity Recognition. In: The Proc. of UIST 2006, pp. 91–100 (2006)Google Scholar
  9. 9.
    Hirsch, T., Forlizzi, J., Hyder, E., Goetz, J., Kurtz, C., Stroback, J.: The ELDer Project: Social, Emotional, and Environmental Factors in the Design of Eldercare Technologies. In: The Proc. of the ACM Conference on Universal Usability, pp. 72–79 (2000)Google Scholar
  10. 10.
    Iachello, G., Abowd, G.D.: Privacy and Proportionality: Adapting Legal Evaluation Techniques to Inform Design in Ubiquitous Computing. In: The Proc. of CHI 2005, pp. 91–100 (2005)Google Scholar
  11. 11.
    IBISWorld. AC and Heating Services in Australia-Industry Market Research Report (August 2007)Google Scholar
  12. 12.
  13. 13.
    Koile, K., Tollmar, K., Demirdjian, D., Howard, S., Trevor, D.: Activity Zones for Context-Aware Computing. In: Dey, A.K., Schmidt, A., McCarthy, J.F. (eds.) UbiComp 2003. LNCS, vol. 2864, pp. 90–106. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  14. 14.
    Market and Bus. Development. UK Domestic Central Heating Market Development (September 2007)Google Scholar
  15. 15.
    Menzer, M.: Heat Pump Status and Trends in North America. In: IEA Heat Pump Conference, May 31 (1999), http://www.ari.org/research/engineering_research/
  16. 16.
    Nadel, S.: Increasing Appliance Energy Savings by Looking Beyond the Current Energy Star. In: ACEEE 2004 Energy Star Appliance Partner Meeting (2004), http://www.energystar.gov/ia/partners/downloads/Plenary_B_Steve_Nadel.pdf
  17. 17.
    Ninomura, P., Bartley, J.: New Ventilation Guidelines For Health Care Facilities. Air Conditioning and Refrigeration Journal, July-September Issue (2002)Google Scholar
  18. 18.
    Orr, R.J., Abowd, G.D.: The Smart Floor: A Mechanism for Natural User Identification and Tracking. In: Proc. of the Extended Abstracts of CHI 2000, pp. 275–276 (2000)Google Scholar
  19. 19.
    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: The Proc. of Ubicomp 2007, pp. 271–288 (2007)Google Scholar
  20. 20.
    Patel, S.N., Truong, K.N., Abowd, G.D.: PowerLine Positioning: A Practical Sub-Room-Level Indoor Location System for Domestic Use. In: The Proc. of Ubicomp 2006, pp. 441–458 (2006)Google Scholar
  21. 21.
    Rowan, J., Mynatt, E.D.: Digital Family Portrait Field Trial: Support for Aging in Place. In: Proc. of CHI 2005, pp. 521–530 (2005)Google Scholar
  22. 22.
    Supplier Relations US, LLC. Ventilation, Heating, Air-Conditioning, and Commercial Refrigeration Equipment Manufacturing Industry in the U.S. and its Foreign Trade (August 2007)Google Scholar
  23. 23.
    Tapia, E.M., Intille, S.S., Larson, K.: Activity recognition in the home setting using simple and ubiquitous sensors. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 158–175. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  24. 24.
    Tapia, E.M., Intille, S.S., Lopez, L., Larson, K.: The design of a portable kit of wireless sensors for naturalistic data collection. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 117–134. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  25. 25.
  26. 26.
    Wilson, D.H., Atkeson, C.G.: Simultaneous Tracking and Activity Recognition (STAR) 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)CrossRefGoogle Scholar
  27. 27.
    Wren, C.R., Munguia-Tapia, E.: Toward Scalable Activity Recognition for Sensor Networks. In: The Proc. of the International Workshop in Location and Context-Awareness (LoCA 2006), pp. 168–185 (2006)Google Scholar
  28. 28.
    Yang, Z., Bobick, A.F.: Visual Integration from Multiple Cameras. In: The Proc. of Application of Computer Vision, WACV/MOTIONS 2005, pp. 488–493 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Shwetak N. Patel
    • 1
  • Matthew S. Reynolds
    • 2
  • Gregory D. Abowd
    • 1
  1. 1.College of Computing, School of Interactive Computing, & GVU CenterGeorgia Institute of TechnologyAtlantaUSA
  2. 2.Department of Electrical and Computer EngineeringDuke UniversityDurhamUSA

Personalised recommendations