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Smart Home for Elderly Using Optimized Number of Wireless Sensors

  • A. Gaddam
  • S. C. Mukhopadhyay
  • G. Sen Gupta
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 64)

Abstract

In this chapter, we are reporting a novel in-home monitoring system designed to for elder-care application. The statistics shows that there is increasing number of elderly people around the world and this isn’t going to change. We developed a smart system consists of optimum number of wireless sensors that includes current, bed, and water flow sensors. The sensors provide information that can be used for monitoring elderly by detecting abnormality pattern in their active daily life. The system will generate early warning message to care giver, when an unforeseen abnormal condition occurs. It will also, analyze the gathered data to determine resident’s behavior. Instead of using many number of sensors, the importance of positioning the optimal number of intelligent sensors close to the source of a potential problem phenomenon, where the acquired data provide the greatest benefit or impact has been discussed.

Keywords

Sensor Node Wireless Sensor Network Smart Home Flow Sensor Sensor Unit 
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.

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References

  1. 1.
    Bowman, R.: Doctors are where patient’s are, http://www.dailyyonder.com/doctors-are-where-patients-arent/2009/02/12/1924 (Retrieved October 23, 2009)
  2. 2.
    Koontz, D. Life expectancy, http://en.wikipedia.org/wiki/Life_expectancy (Retrieved October 24, 2009)
  3. 3.
    Dittmar, A., Axisa, F., Delhomme, G., Gehin, C.: New concepts and technologies in home care and ambulatory monitoring. Studies in Health Technology and Informatics, 9–35 (2004)Google Scholar
  4. 4.
    Jovanov, E., Raskovic, D., Price, J., Chapman, J., Moore, A., Krishnamurthy, A.: Patient Monitoring Using Personal Area Networks of Wireless Intelligent Sensors. Biomedical Sciences Instrumentation, 373–378 (2001)Google Scholar
  5. 5.
    Ohta, S., Nakamoto, H., Shinagawa, Y., Tanikawa, T.: A health monitoring system for elderly people living alone, PMID: 12097176 [PubMed - indexed for MEDLINE]Google Scholar
  6. 6.
    US20030058111, Computer vision based elderly care monitoring systemGoogle Scholar
  7. 7.
    Maki, H., Yonczawa, Y., Ogawa, H., Sato, H., Hahn, A.W., Caldwell, W.M.: A welfare facility resident care support system. Biomedical Sciences Instrumentation, 480–483 (2004)Google Scholar
  8. 8.
    Munguia Tapia, E., 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)Google Scholar
  9. 9.
    US Patent US06796799, Behavior determining apparatus, care system, care residence and behavior information specifying apparatus and systemGoogle Scholar
  10. 10.
    Callaway, E., Gorday, P., Hester, L., Gutierrez, J.A., Naeve, M., Heile, B., Bahl, V.: Home Networking with IEEE 802.15.4: A Developing Standard for Low-Rate Wireless Personal Area Networks. IEEE Communications Magazine, 69–77 (August 2002)Google Scholar
  11. 11.
    US Patent 6002994 - Method of user monitoring of physiological and non-physiological measurementsGoogle Scholar
  12. 12.
    US Patent 4990893 - Method in alarm system, including recording of energy consumptionGoogle Scholar
  13. 13.
    Eriksson, H., Timpka, T.: The potential of smart homes for injury prevention among the elderly. Injury Control and Safety Promotion 9(2), 127–131 (2002)CrossRefGoogle Scholar
  14. 14.
    Dengler, S., Awad, A., Dressler, F.: Sensor/Actuator Networks in Smart Homes for Supporting Elderly and Handicapped People. In: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops 2007, vol. 2, pp. 863–868 (2007)Google Scholar
  15. 15.
    Joshi, S., Boyd, S.: Department of Electrical Engineering, Stanford University Sensor Selection via Convex Optimization. IEEE Transactions on Signal Processing, 321–325 (November 2007)Google Scholar
  16. 16.
    Giraud, C., Jouvencel, B.: Sensor selection: A geometrical approach. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 45–49 (1995)Google Scholar
  17. 17.
    Zhang, H., Zhang, H.: Node Selection Algorithm Optimized for Wireless Sensor Network. In: Proceedings of 2008 Workshop on Knowledge Discovery and Data Mining, pp. 481–484. IEEE Computer society, Los Alamitos (2008)CrossRefGoogle Scholar
  18. 18.
    Figueredo, M., Dias, J.: Mobile telemedicine system for home care and patient monitoring. In: Proc. 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEMBS 2004, vol. 2, pp. 3387–3390 (2004)Google Scholar
  19. 19.
    Mukhopadhyay, S.C., Gaddam, A., Gupta, G.S.: Wireless Sensors for Home Monitoring - A Review. Recent Patents on Electrical Engineering 1, 32–39 (2008)CrossRefGoogle Scholar
  20. 20.
    Inline Flow Transducers, Sensor,flow,liquid,0.25-6.5L/min,pulse O/P, http://newzealand.rsonline.com/web/search/searchBrowseAction.html?method=getProduct&R=0257149
  21. 21.
    Gusakov, I.: Bed patient position monitor, United States Patent 5184112 (1993)Google Scholar
  22. 22.
    Tekscan. FlexiForce force sensors, http://www.tekscan.com/Flexi-Force/Flexi-Force.html (Retrieved October 25, 2009)

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • A. Gaddam
    • 1
  • S. C. Mukhopadhyay
    • 1
  • G. Sen Gupta
    • 1
  1. 1.School of Engineering and Advance TechnologyMassey UniversityPalmerston NorthNew Zealand

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