Mobile Networks and Applications

, Volume 19, Issue 3, pp 287–302 | Cite as

Smart Collaborative Mobile System for Taking Care of Disabled and Elderly People

  • Sandra Sendra
  • Emilio Granell
  • Jaime Lloret
  • Joel J. P. C. Rodrigues
Article

Abstract

Official statistics data show that in many countries the population is aging. In addition, there are several illnesses and disabilities that also affect a small sector of the population. In recent years, researchers and medical foundations are working in order to develop systems based on new technologies and enhance the quality of life of them. One of the cheapest ways is to take advantage of the features provided by the smartphones. Nowadays, the development of reduced size smartphones, but with high processing capacity, has increased dramatically. We can take profit of the sensors placed in smartphones in order to monitor disabled and elderly people. In this paper, we propose a smart collaborative system based on the sensors embedded in mobile devices, which permit us to monitor the status of a person based on what is happening in the environment, but comparing and taking decisions based on what is happening to its neighbors. The proposed protocol for the mobile ad hoc network and the smart system algorithm are described in detail. We provide some measurements showing the decisions taken for several common cases and we also show the performance of our proposal when there is a medium size group of disabled or elderly people. Our proposal can also be applied to take care of children in several situations.

Keywords

Disabled and elderly people Mobile wireless network Collaborative system 

References

  1. 1.
    Cisco Systems Inc. “Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2010–2015.” White Paper, February 1, 2011Google Scholar
  2. 2.
    Pereira O, Caldeira J, Rodrigues J (2011) Body sensor network mobile solutions for biofeedback monitoring. J Mob Netw Appl 16(6):713–732CrossRefGoogle Scholar
  3. 3.
    Google. Galaxy nexus (2012). Available: http://www.google.com/nexus/
  4. 4.
    E. Commission. “Demography report 2010.” Eurostat, the Statistical Office of the European Union, 2010. At http://ec.europa.eu/social/BlobServlet?docId=6824&langId=en
  5. 5.
    Thomas KE, Stevens JA, Sarmiento K, Wald MM (2008) Fall-related traumatic brain injury deaths and hospitalizations among older adults—United States, 2005. J Saf Res 39(3):269–272CrossRefGoogle Scholar
  6. 6.
    Fortino G, Giannantonio R, Gravina R, Kuryloski P, Jafari R, (2013) Enabling effective programming and flexible management of efficient body sensor network applications. IEEE Trans Hum Mach Syst 43(1):115–133Google Scholar
  7. 7.
    Bellifemine F, Fortino G, Giannantonio R, Gravina R, Guerrieri A, Sgroi M (2011) SPINE: a domain-specific framework for rapid prototyping of WBSN applications. Softw Pract Exper 41(3):237–265Google Scholar
  8. 8.
    Macias E, Lloret J, Suarez A, Garcia M (2012) Architecture and protocol of a semantic system designed for video tagging with sensor data in mobile devices. Sensors 12(2):2062–2087CrossRefGoogle Scholar
  9. 9.
    Sendra S, Granell E, Lloret J, Rodrigues JJPC. Smart Collaborative System Using the Sensors of Mobile Devices for Monitoring Disabled and Elderly People, 3rd IEEE International Workshop on Smart Communications in Network Technologies, Ottawa, Canada, June 11, 2012Google Scholar
  10. 10.
    Lane N, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell A (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140–150CrossRefGoogle Scholar
  11. 11.
    Muldoon C, OHare G, OGrady M (2006) Collaborative agent tuning: Performance enhancement on mobile devices Engineering Societies in the Agents World VI, Lecture Notes in Computer Science, Volume 3963/2006, pp 241–258Google Scholar
  12. 12.
    Turner H, White J, Thompson C, Zienkiewicz K, Campbell S, Schmidt DC (2009) Building Mobile Sensor Networks Using Smartphones and Web Services: Ramifications and Development Challenges, Handbook of Research on Mobility and Computing, Hershey, PA. Available: http://lsrg.cs.wustl.edu/~schmidt/PDF/new-ww-mobile-computing.pdf
  13. 13.
    Kansal A, Goraczko M, Zhao F. Building a sensor network of mobile phones, 6th International Conference on Information Processing in Sensor Networks. Cambridge, Massachusetts, USA, April 24–27, 2007 pp 547–548Google Scholar
  14. 14.
    Plaza I, Martín L, Martin S, Medrano C (2011) Mobile applications in an aging society: status and trends. J Syst Softw 84(11):1977–1988CrossRefGoogle Scholar
  15. 15.
    Camarinha-Matos L, Afsarmanesh H. Telecare: Collaborative virtual elderly support communities, 1st Workshop on Tele-Care and Collaborative Virtual Communities in Elderly Care, Porto, Portugal, 13 April, 2004Google Scholar
  16. 16.
    Chen B, Pompili D (2011) Transmission of patient vital signs using wireless body area networks. J Mob Netw Appl 16(6):663–682CrossRefGoogle Scholar
  17. 17.
    Dai J, Bai X, Yang Z, Shen Z, Xuan D (2010) Mobile phone-based pervasive fall detection. Pers Ubiquit Comput 14(7):633–643CrossRefGoogle Scholar
  18. 18.
    Martin P, Sánchez MA, Álvarez L, Alonso V, Bajo J. Multiagent system for detecting elderly people falls through mobile devices, International Symposium on Ambient Intelligence (ISAmI’11), Salamanca (Spain) 6–8 April 2011Google Scholar
  19. 19.
    Fahmi PN, Viet V, Deok-Jai C. “Semi-supervised fall detection algorithm using fall indicators in smartphone.” Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication, 2012, pp 122Google Scholar
  20. 20.
    Sánchez M, Martín P, Álvarez L, Alonso V, Zato C, Pedrero A, Bajo J (2011) A New Adaptive Algorithm for Detecting Falls through Mobile Devices, Trends in Practical Applications of Agents and Multiagent Systems, pp 17–24Google Scholar
  21. 21.
    Fahim M, Fatima I, Lee S, Lee YK. Daily Life Activity Tracking Application for Smart Homes using Android Smartphone, 14th International Conference on Advanced Communication Technology, Yongin, South Korea, 19–22 February 2012, pp 241–245Google Scholar
  22. 22.
    Kaluža B, Mirchevska V, Dovgan E, Luštrek M, Gams M (2010) An agent-based approach to care in independent living, Ambient Intelligence, Lecture Notes in Computer Science, vol. 6439, pp 177–186Google Scholar
  23. 23.
    Costa A, Barbosa G, Melo T, Novais P (2011) Using mobile systems to monitor an ambulatory patient. In: International Symposium on Distributed Computing and Artificial Intelligence, Advances in Intelligent and Soft Computing, vol. 91, pp 337–344Google Scholar
  24. 24.
    Olfati-Saber R, Fax J, Murray R (2007) Consensus and cooperation in networked multi-agent systems. Proc IEEE 95(1):215–233CrossRefGoogle Scholar
  25. 25.
    Arcelus A, Jones MH, Goubran R, Knoefel F (2007) Integration of smart home technologies in a health monitoring system for the elderly, 21st International Conference on Advanced Information Networking and Applications Workshops, vol. 2, pp 820–825Google Scholar
  26. 26.
    Kahmen H, Faig W (1988) Surveying. Walter de Gruyter & Co, New YorkCrossRefGoogle Scholar
  27. 27.
  28. 28.
  29. 29.
    Sendra S, Lloret J, Garcia M, Toledo JF (2011) Power saving and energy optimization techniques for wireless sensor networks. J Commun 6(6):439–459CrossRefGoogle Scholar
  30. 30.
    Matlab Website. Available at: www.mathworks.com/products/matlab
  31. 31.
    Pal A (2010) Localization algorithms in wireless sensor networks: current approaches and future challenges. Netw Protocol Algorithm 2(1):45–74Google Scholar
  32. 32.
    Garcia M, Boronat F, Tomás J, Lloret J (2009) The development of two systems for indoor wireless sensors self-location. Ad Hoc Sensor Wirel Netw 8(3–4):235–258Google Scholar
  33. 33.
    Lloret J, Tomás J, Garcia M, Cánovas A (2009) A hybrid stochastic approach for self-location of wireless sensors in indoor environments. Sensors 9(5):3695–3712CrossRefGoogle Scholar
  34. 34.
    Garcia M, Sendra S, Turro C, Lloret J (2011) User’s macro and micro-mobility study using WLANs in a university campus. Int J Adv Internet Technol 4(1&2):37–46Google Scholar
  35. 35.
    Lloret J, Tomas J, Canovas A, Bellver I. GeoWiFi: A Geopositioning System Based on WiFi Networks, The Seventh International Conference on Networking and Services (ICNS 2011), Venice (Italy), May 6–10, 2011Google Scholar
  36. 36.
    Yu W, Su X, Hansen J (2012) A smartphone design approach to user communication interface for administering storage system network. Netw Protoc Algorithm 4(4):126–155Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Sandra Sendra
    • 1
  • Emilio Granell
    • 1
  • Jaime Lloret
    • 1
  • Joel J. P. C. Rodrigues
    • 2
  1. 1.Integrated Management Coastal Research InstituteUniversidad Politécnica de ValenciaGrao de GandiaSpain
  2. 2.Instituto de TelecomunicaçõesUniversidade da Beira InteriorCovilhãPortugal

Personalised recommendations