Health Smart Home Services incorporating a MAR-based Energy Consumption Awareness System

Abstract

Health smart homes would enable people suffering from various diseases and handicaps to live an autonomous lifestyle in their own residences. The concept of the health smart home emphasizes ‘aging in place’, where residents enjoy a healthy independent life in their own homes as they become older. While energy saving is one of the crucial issues to be addressed in domestic buildings, there is little research into household energy consumption in health smart homes. This paper identifies each variable’s implications for health smart home services and highlights its application to energy consumption awareness. We also introduce Mobile Augmented Reality (MAR) to simulate energy consumption awareness in health smart homes. Firstly, the research proposes a framework for constructing health smart home services with a focus on the practicability of each variable from the perspective of supporting user experience in home settings. Rather than address each variable in isolation, we consider comprehensive issues in terms of service effectiveness in supporting a healthy life at home. Additionally, the innovative MAR application associated with energy use is presented as a new solution for household energy consumption awareness. The proposed application will be a basis for the perspectives of future research directions on health smart home services.

This is a preview of subscription content, access via your institution.

References

  1. 1.

    Harper, R.: Inside the Smart Home. Springer (2003)

  2. 2.

    Gutierrez, J.: On the Use of IEEE 802.15.4 to enable wireless sensor networks in building automation. In: Proceedings of the 15th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2004), Barcelona, 5–8 September 2005, pp 1865–1869 (2005)

  3. 3.

    Tamura, T., Togawa, T., Ogawa, M., Yoda, M.: Fully automated health monitoring system in the home. Med. Eng. & Phys. 20, 573–579 (1998)

    Article  Google Scholar 

  4. 4.

    Lyardet, F.K.F., Nakajima, T.: Three challenges for future smart object systems. In: Proceedings of the 2nd International Workshop on Smart Products: Building Block of Ambient Intelligence (AmI-Block’08) (2008)

  5. 5.

    Noury, N., Virone, G., Barralon, P., Ye, J., Rialle, V., Demongeot, J.: New Trends in Health Smart Homes. In: Proceedings of the 5th International Workshop on Enterprise Networking and Computing in Healthcare Industry (Healthcom 2003), Santa Monica, 6–7 June 2003, pp 118–127 (2003)

  6. 6.

    Mozer, M.: The neural network house: an environment that is adapts to its inhabitants (1998)

  7. 7.

    Adlam, T., Faulkner, R., Orpwood, R., Jones, K., Macijauskiene, J., Budraitiene, A.: The Installation and Support of Internationally Distributed Equipment for People with Dementia. IEEE Trans. Inf. Technol. Biomed. 8(3), 253–257 (2004)

    Article  Google Scholar 

  8. 8.

    Jiang, L., Liu, D., Yang, B.: Smart Home Research (2004)

  9. 9.

    Bartolomeu, P., Fonseca, J., Vasques, F.: Challenges in Health Smart Homes. In: Proceedings of Pervasive Computing Technologies for Healthcare (Pervasive Health 2008), Tampere, 30 January – 1 February 2008, pp 19–22 (2008)

  10. 10.

    Chan, M., Esteve, D., Escriba, C., Campoa, E.: A review of smart homes—present of state and future challenges. Comput. Methods Programs Biomed. 91, 55–81 (2008)

    Article  Google Scholar 

  11. 11.

    Subiyanto, S., Mohamed, A., Hannan, M.: Intelligent maximum power point tracking for PV system using hopfield neural network optimized fuzzy logic Controller. Energy Build. 51, 29–38 (2012)

    Article  Google Scholar 

  12. 12.

    Ouyang, J., Wang, C., Li, H., Hokao, K.: A methodology for energy-efficient renovation of existing residential buildings in china and case study. Energy Build. 43(9), 2203–2210 (2011)

    Article  Google Scholar 

  13. 13.

    Kim, S.M., Lee, J.-H., Kim, S., Moon, H.J., Cho, J.: Determining operation schedules of heat recovery ventilators for optimum energy savings in high-rise residential buildings. Energy Build. 46(3), 3–13 (2012)

    Article  Google Scholar 

  14. 14.

    Utlu, Z., Hepbasli, A.: A study on the evaluation of energy utilization efficiency in the turkish residential-commercial sector using energy and exergy analyses. Energy Build. 35(11), 1145–1153 (2003)

    Article  Google Scholar 

  15. 15.

    McNeil, M.A., Letschert, V.E.: Modeling diffusion of electrical appliances in the residential sector. Energy Build. 42(6), 783–790 (2010)

    Article  Google Scholar 

  16. 16.

    Santin, O.G., Ltard, L., Visscher, H.: The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock. Energy Build. 41(11), 1223–1232 (2009)

    Article  Google Scholar 

  17. 17.

    Cianfrini, C., Corcione, M., Habib, E., Quintino, A.: Energy performance of a lightweight opaque ventilated façade integrated with the HVAC system using saturated exhaust indoor air. Energy Build. 50, 26–34 (2012)

    Article  Google Scholar 

  18. 18.

    Bull, R., Chang, N., Fleming, P.: The use of building energy certificates to reduce energy consumption in European public buildings. Energy Build. 50, 103–110 (2012)

    Article  Google Scholar 

  19. 19.

    Toguyeni, D.Y.K., Coulibaly, O., Ouedraogo, A., Koulidiati, J., Dutil, Y., Rousse, D.: Study of the influence of roof insulation involving local materials on cooling loads of houses built of clay and straw. Energy Build. 50, 74–80 (2012)

    Article  Google Scholar 

  20. 20.

    Barr, S., Gilg, A.W., Ford, N.: The household energy gap: examining the divide between habitual- and purchase-related conservation behaviours. Energy Policy 33, 1425–1444 (2005)

    Article  Google Scholar 

  21. 21.

    Branco, G., Lachal, B., Gallinelli, P., Weber, W.: Predicted versus observed heat consumption of a low energy multifamily complex in Switzerland based on long-term experimental data. Energy Build. 36 (6), 543–555 (2004)

    Article  Google Scholar 

  22. 22.

    Yu, Z., Fung, BCM, Haghighat, F., Yoshino, H., Morofsky, E.: A systematic procedure to study the influence of occupant behavior on building energy consumption. Energy Build. 42 (9), 1409–1417 (2011)

    Article  Google Scholar 

  23. 23.

    Kim, M.J., Cho, M.E., Kim, J.T.: Energy use of households in apartment complexes with different service life. Energy Build. 66, 591–598 (2013)

    Article  Google Scholar 

  24. 24.

    Chan, M., Campo, E., Estève, D., Fourniols, J.: Smart homes—current features and future perspectives. Maturitas 64 (2), 90–97 (2009)

    Article  Google Scholar 

  25. 25.

    Mozer, M.C.: The neural network house: an environment that’s adapts to its inhabitants. In: The AAAI Spring Symposium on Intelligent Environments 1998, pp 110–114 (1998)

  26. 26.

    Perry, M., Dowdall, A., Lines, L., Hone, K.: Multimodal and ubiquitous computing systems: supporting independent-living older users. IEEE Trans. Inf. Technol. Biomed. 8 (3), 258–270 (2004)

    Article  Google Scholar 

  27. 27.

    House_n (MIT) information. http://architecture.mit.edu/house_n/.

  28. 28.

    Cory, D.K., Rovert, O., Gregory, D.A., Christopher, G.A., E, I.A., Blair, M., Elizabeth, M., S, T.E., Wendy, N.: The Aware Home: a living laboratory for ubiquitous computing research architecture, pp 199–198 (1998)

  29. 29.

    Tapia, E., Intille, S., Larson, K.: Activity Recognition in the Home Using Simple and Ubiquitous Sensors. In: Proceedings of Pervasive Computing (Pervasive, Vol. 2004, pp 158–175, Pittsburgh (2004)

  30. 30.

    Kidd, C.D., Orr, R.J., Abowd, G.D., Atkeson, C.G., Essa, I.A., MacIntyre, B., Mynatt, E., Starner, T.E., Newstetter, W.: The aware home: a living laboratory for ubiquitous computing research. In: 2nd International Workshop on Cooperative buildings (CoBuild’99) (1999)

  31. 31.

    Elger, G., Furugren, B.: SmartBo-An ICT and computer-based demonstration home for disabled people. Paper presented at the improving the quality of life for the European citizen technology for inclusive design and equality assistive technology research series

  32. 32.

    Tapia, E.M., Intille, S.S., Larson, K.: Activity recognition in the home using simple and ubiquitous sensors. In: Pervasive Computing (Pervasive, Vol. 2004), pp 158–175. Pittsburgh (2004)

  33. 33.

    Seo, M.K., Kim, T.G., Lim, M.S., Lim, S.C., Jang, S.J., Choi, I.H., Choi, J.W.: Smart Home Network in abroad. In: Ministry of Construction and Transportation of Korea (2006)

  34. 34.

    Das, S.K., Cook, D.J., Bhattacharya, A., Heierman, E.O., Lin, T.Y.: The role of prediction algorithm in the MavHome smart home architecture. IEEE Wirel. Commun. 9 (6), 77–84 (2002)

    Article  Google Scholar 

  35. 35.

    Brumitt, B., Meyers, B., Krumm, J., Kern, A., Shafer, S.: EasyLiving: technologies for intelligent environments Handheld and Ubiquitous Computing (2000)

  36. 36.

    Azuma, R.: A survey of sugmented reality. Presence-Teleoperators Virtual Environ. 6 (4), 355–385 (1997)

    Google Scholar 

  37. 37.

    Wang, X.D.P.S.: Design, strategies, and issues towards an augmented reality-based construction training platform. J. Inf. Technol. Constr. (ITcon) 12, 363–380 (2007)

    Google Scholar 

  38. 38.

    Wang, X., Schnabel, M.A. (eds.): Mixed Reality in Architecture, Design, and Construction. Springer-Verlag (2009)

  39. 39.

    Shin, D.H., Dunston, P.S., Wang, X.: View changes in mixed reality-based collaborative virtual environments. ACM Trans. Appl. Percept. Assoc. Comput. Mach. 2 (1), 1–14 (2005)

    Article  Google Scholar 

  40. 40.

    Chi, H.L., Kang, S., Wang, X.: Research trend and opportunities of augmented reality applications in architecture, engineering and construction. Autom. Constr. 33, 116–122 (2013)

    Article  Google Scholar 

  41. 41.

    Wang, X.: Augmented reality in architecture and design: potentials and challenges for application. Int. J. Archit. Comput. 7 (2), 309–326 (2009)

    Article  Google Scholar 

  42. 42.

    Rice, R.: Augmented Vision and the Decade of Ubiquity http://curiousraven.squarespace.com/(2009).20

  43. 43.

    Porteus, J., Brownsell, S.: Exploring Technologies for Independent Living for Older People: A Report on the Anchor Trust/BT Telecare Re. Oxon, U.K.: Anchor Trust (2000)

  44. 44.

    Tuomisto, M.T., Terho, T., Korhonen, I., Lappalainen, R., Tuomisto, T., Laippala, P., Turjanmaa, V.: Diurnal and weekly rhythms of health-related variables in home recordings for two months. Physiol. & Behav. 87, 650–658 (2006)

    Article  Google Scholar 

  45. 45.

    Kim, M.J., Oh, M.W., Cho, M.E., Lee, H., Kim, J.T.: A Critical review of user studies on healthy smart homes. Indoor Built Environ. 22, 260–270 (2013)

    Article  Google Scholar 

  46. 46.

    Noury, N., Virone, G., Barralon, P., Ye, J., Rialle, V., Demongeot, J.: New trends in health smart homes. In: The 5th International Workshop on Enterprise Networking and Computing in Healthcare Industry (Healthcom 2003), Santa Monica, 6–7 June 2003, pp 118–127

  47. 47.

    Nisbet, P.: Integrating assistive technologies: current practices and future possibilities. Med. Eng. & Phys. 18(3), 193–202 (1996)

    Article  Google Scholar 

  48. 48.

    Perry, M., Dowdall, A., Lines, L., Hone, K.: Multimodal and ubiquitous computing systems: supporting independent-living older users. IEEE Trans. Inf. Technol. Biomed. 8 (3), 258–270 (2004)

    Article  Google Scholar 

  49. 49.

    Brooks, F.P., Ouh-Young, M., Batter, J.J., Kilpatrick, P.J.: Project GROPE - Haptic displays for scientific visualization. In: Proceedings of ACM SIGGRAPH’90 1990, pp 177–185

  50. 50.

    Kim, M.J., Maher, M.L.: The impact of tangible user interfaces on designers’ spatial cognition. Human-Comput. Interact. 23 (2), 101–137 (2008)

    Article  Google Scholar 

  51. 51.

    Seichter, H., Kvan, T.: Tangible interfaces in design computing. In: Proceedings of the Education and research in Computer Aided Architectural Design in Europe (eCAADe) (2004)

  52. 52.

    Mynatt, E.D., Essa, I., Rogers, W.: Increasing the Opportunities for Aging in Place. In: Proceedings on the ACM Conference on Universal Usability 2000 2000, pp 65–71. ACM Press

  53. 53.

    Redden, T., Benford, S.: The Evolution of buildings and implications for the design of ubiquitous domestic environments. In: Proceedings of the ACM CHI 2003 (2003)

  54. 54.

    Gaver, B., Martin, H.: Alternatives: exploring information appliances through conceptual design proposals. In: CHI ’00 Proceedings of the SIGCHI conference on Human Factors in Computing Systems, pp 209–216

  55. 55.

    Crabtree, A., Rodden, T.: Computer Supported Cooperative Work 13 2, pp. 191–220 (2004)

  56. 56.

    Hindus, D., Mainwaring, S.D., Leduc, N., Hagström, A.E., Bayley, O.: Casablanca: designing social communication devices for the home. In: The 2001 CHI Conference on Human Factors in Computing Systems, Seattle 2001, pp 325–332. ACM Press

  57. 57.

    Crabtree, A., Rodden, T., Hemmings, T.: Supporting communication in domestic settings. In: The 2003 Home Oriented Informatics and Telematics Conference, p 2002. Irvine, California

  58. 58.

    O’Brien, J., Rodden, T., Rouncefield, M., Hughes, J.A.: At home with the technology. ACM Trans. Comput.-Human Interact. 6 (3), 282–308 (1999)

    Article  Google Scholar 

  59. 59.

    Jiang, L., Liu, D., Yang, B.: Smart home research. In: The 2004 International Conference on Machine Learning and Cybernetics, Shanghai, 26–29 August 2004, pp 659–663

  60. 60.

    Bartolomeu, P., Fonseca, J., Vasques, F.: Challenges in Health Smart Homes. In: Pervasive Computing Technologies for Healthcare (Pervasive Health 2008), Tampere, 30 January – 1 February 2008, pp 19–22

  61. 61.

    Chan, M., Esteve, D., Escriba, C., Campoa, E.: A review of smart homes—Present state and future challenges. Comput. Methods Programs Biomed. 91, 55–81 (2008)

    Article  Google Scholar 

  62. 62.

    Chan, M., Campoa, E., Estèvea, D., Fourniolsa, J.: Smart homes — current features and future perspectives. Maturitas 64(2), 90–97 (2009)

    Article  Google Scholar 

  63. 63.

    Coleman, M., Brown, N., Wright, A., Firth, S.K.: Information, communication and entertainment appliance use—Insights from a UK household study. Energy Build. 54, 61–72 (2012)

    Article  Google Scholar 

  64. 64.

    Subiyanto, S., Mohamed, A., Hannan, M.A.: Intelligent maximum power point tracking for PV system using Hopfield neural network optimized fuzzy logic controller. Energy Build. 51, 29–38 (2012)

    Article  Google Scholar 

  65. 65.

    Weiser, M.: The Computer for the Twenty-First Centry. Scienfic American (1991)

  66. 66.

    Weiser, M., Brown, J.S.: Designing calm technology. PowerGrid 1(1) (1996)

  67. 67.

    Oh, M.W., Kim, M.J.: Energy use associated with social types of elderly households. In: The 20th IAGG World Congress of Gerontology and Geriatrics, Seoul, June 23–27 (2013)

  68. 68.

    Garg, V., Bansal, N.K.: Smart occupancy sensors to reduce energy consumption. Energy Buidlings 32, 81–87 (2000)

    Article  Google Scholar 

  69. 69.

    Lu, J., Sookoor, T., Srinivasan, V., Gao, G., Holben, B., Stankovic, J., Field, E., Whitehouse, K.: The smart thermostat: using occupancy sensors to save energy in homes. In: the 8th ACM Conference on Embedded Networked Sensor Systems 2010, pp. 211–224

  70. 70.

    Arvola, A., Uutela, A., Anttila, U.: Billing feedback as a means of encouraging conservation of electricity in households: A Field Experiment in Helsinki. In: Energy and the Consumer. Finish Ministry of Trade and Industry (1994)

  71. 71.

    Barbose, G., Goldman, C., Neenan, B.: A survey of utility expeirence with real time pricing: implications for policymakers seeking price responsive demand. In: European Council for an Energy-Efficent Economy (2005)

  72. 72.

    Darby, S.: The effectivenss of feedback on energy consumption: a review for defra of the literature on metering, billing and direct display. In: Environmental Change Institute, University of Oxford (2006)

  73. 73.

    Wood, G., Newborough, M.: Dynamic energy-consumption indicators for domestic appliances: environment, behavior and design. Energy Build. 35, 821–841 (2003)

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Mi Jeong Kim.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kim, M.J., Lee, J.H., Wang, X. et al. Health Smart Home Services incorporating a MAR-based Energy Consumption Awareness System. J Intell Robot Syst 79, 523–535 (2015). https://doi.org/10.1007/s10846-014-0114-x

Download citation

Keywords

  • Energy Consumption Awareness
  • Health Smart Home Service
  • Mobile Augmented Reality
  • Energy-related Behavior