Advertisement

General Assisted Living System Architecture Model

  • Vladimir Trajkovik
  • Elena Vlahu-Gjorgievska
  • Saso Koceski
  • Igor Kulev
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 141)

Abstract

Novel information and communication technologies create possibilities to change the future of health care and support. Ambient Assisted Living (AAL) is seen as a promising alternative to the current care models so a number of researchers have developed AAL systems with promising results. The main goal of AAL solutions is to apply ambient intelligence technologies to enable people with specific needs to continue to live in their preferred environments. In this paper, we are presenting a general architecture of system for assisted living that supports most of the use cases for such system.

Keywords

Assisted living Wearable sensors Environmental sensors Social networks 

Notes

Acknowledgement

The authors would also like to acknowledge the contribution of the COST Action IC1303 - AAPELE, Architectures, Algorithms and Platforms for Enhanced Living Environments.

References

  1. 1.
    Korhonen, I., Parkka, J., Van Gils, M.: Health monitoring in the home of the future. IEEE Eng. Med. Biol. 22(3), 66–73 (2003)CrossRefGoogle Scholar
  2. 2.
    Cocosila, M., Archer, N.: Adoption of mobile ict for health promotion: an empirical investigation. Electron. Markets 20(3–4), 241–250 (2010)CrossRefGoogle Scholar
  3. 3.
    Cardinaux, F., Bhowmik, D., Abhayaratne, C., Hawley, M.S.: Video based technology for ambient assisted living: A review of the literature. J. Ambient Intell. Smart Environ. 3(3), 253–269 (2011)Google Scholar
  4. 4.
    Takács, B., Hanák, D.: A mobile system for assisted living with ambient facial interfaces. Int. J. Comput. Sci. Inf. Syst. 2(2), 33–50 (2007)Google Scholar
  5. 5.
    Kleinberger, T., Jedlitschka, A., Storf, H., Steinbach-Nordmann, S., Prueckner, S.: An approach to and evaluations of assisted living systems using ambient intelligence for emergency monitoring and prevention. In: Stephanidis, C. (ed.) UAHCI 2009, Part II. LNCS, vol. 5615, pp. 199–208. Springer, Heidelberg (2009)Google Scholar
  6. 6.
    Sun, H., De Florio, V., Gui, N., Blondia, C.: Promises and challenges of ambient assisted living Systems. In: Proceedings of the 6th International Conference on Information Technology: New Generations, Las Vegas NV, 27–29 April 2009, pp. 1201–1207 (2009)Google Scholar
  7. 7.
    Memon, M., Wagner, S.R., Pedersen, C.F., Beevi, F.H.A., Hansen, F.O.: Ambient assisted living healthcare frameworks, platforms, standards, and quality attributes. Sensors 14, 4312–4341 (2014)CrossRefGoogle Scholar
  8. 8.
    Gunter, T.D., Terry, N.P.: The emergence of national electronic health record architectures in the United States and Australia: Models, costs, and questions. J. Med. Internet Res. 7(1), e3 (2005)CrossRefGoogle Scholar
  9. 9.
    Tang, P., Ash, J., Bates, D., Overhage, J., Sands, D.: Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption. JAMIA 13(2), 121–126 (2006)Google Scholar
  10. 10.
    Knaup, P., Schöpe, L.: Using data from ambient assisted living and smart homes in electronic health records. Methods Inf. Med. 53, 149–151 (2004)CrossRefGoogle Scholar
  11. 11.
    http://www.hl7.org. Accessed 06 August 2014
  12. 12.
    http://www.continuaalliance.org. Accessed 06 August 2014
  13. 13.
    http://www.etsi.org/standards. Accessed 06 August 2014
  14. 14.
    http://www.aal-europe.eu. Accessed 06 August 2014
  15. 15.
    Viron, G, Sixsmith A (2008) Toward Information Systems for Ambient Assisted Living. In: Proceedings of the 6th International Conference of the International Society for Gerontechnology, Pisa, Tuscany, Italy, 4–7 June 2008Google Scholar
  16. 16.
    Hill C, Grant R, Yeung I (2013) Ambient Assisted Living Technology. An interactive qualifying project report submitted to the Faculty of Worcester Polytechnic InstituteGoogle Scholar
  17. 17.
    Mikalsen M, Hanke S, Fuxreiter T, Walderhaug S, Wienhofen L (2009) Interoperability Services in the MPOWER Ambient Assisted Living Platform. In: Medical Informatics Europe (MIE) Conference, Sarajevo, 30 August–2 September 2009Google Scholar
  18. 18.
    Ruiz-Zafra, Á., Benghazi, K., Noguera, M., Garrido, J.L.: Zappa: An open mobile platform to build cloud-based m-health systems. In: van Berlo, A., Hallenborg, K., Rodríguez, J.M.C., Tapia, D.I., Novais, P. (eds.) Ambient Intelligence - Software and Applications. AISC, vol. 219, pp. 87–94. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  19. 19.
    Wood, A., Stankovic, J., Virone, G., Selavo, L., He, Z., Cao, Q., Doan, T., Wu, Y., Fang, L., Stoleru, R.: Context-aware wireless sensor networks for assisted living and residential monitoring. IEEE Netw. 22(4), 26–33 (2008)CrossRefGoogle Scholar
  20. 20.
    López-de-Ipiña, D., Díaz-de-Sarralde, I., García-Zubia, J.: An ambient assisted living platform integrating RFID data-on-tag care annotations and twitter. J. Univers. Comput. Sci. 16(12), 1521–1538 (2010)Google Scholar
  21. 21.
    Jara, A.J., Zamora, M.A., Skarmeta, A.F.G.: An internet of things–based personal device for diabetes therapy management in ambient assisted living (AAL). Pers. Ubiquit. Comput. 15, 431–440 (2011)CrossRefGoogle Scholar
  22. 22.
    Mileo, A., Merico, D., Bisiani, R.: Support for context-aware monitoring in home healthcare. J. Ambient Intell. Smart Environ. 2(1), 49–66 (2010)Google Scholar
  23. 23.
  24. 24.
  25. 25.
  26. 26.
    Liolios, C., Doukas, C., Fourlas, G., Maglogiannis, I.: An overview of body sensor networks in enabling pervasive healthcare and assistive environments. In: Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments, Samos, Greece, 23–25 June 2010Google Scholar
  27. 27.
    Nugent, C.D., Galway, L., Chen, L., Donnelly, M.P., McClean, S.I., Zhang, S., Scotney, B.W., Parr, G.: Managing sensor data in ambient assisted living. J. Comput. Sci. Eng. 5(3), 237–245 (2011)CrossRefGoogle Scholar
  28. 28.
    Gama, O., Carvalho, P., Alfonso, J.A., Mendes, P.M.: Quality of service support in wireless sensor networks for emergency healthcare services. In: Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1296–1299. IEEE Computer Society (2008)Google Scholar

Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015

Authors and Affiliations

  • Vladimir Trajkovik
    • 1
  • Elena Vlahu-Gjorgievska
    • 2
  • Saso Koceski
    • 3
  • Igor Kulev
    • 1
  1. 1.Faculty of Computer Science and EngineeringUniversity “Ss Cyril and Methodious”SkopjeRepublic of Macedonia
  2. 2.Faculty of Information and Communication TechnologyUniversity “St. Kliment Ohridski”BitolaRepublic of Macedonia
  3. 3.Faculty of Computer ScienceUniversity “Goce Delcev”StipRepublic of Macedonia

Personalised recommendations