Advertisement

A Context Aware Architecture to Support People with Partial Visual Impairments

  • João Fernandes
  • João Laranjeira
  • Paulo Novais
  • Goreti Marreiros
  • José Neves
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 217)

Abstract

Nowadays there are several systems that help people with disabilities on their quotidian tasks. The visual impairment is a problem that affects several people in their tasks and movements. In this work we propose an architecture capable of processing information from the environment and suggesting actions to the user with visual impairments, to avoid a possible obstacle. This architecture intends to improve the support given to the user in their daily movements. The idea is to use speculative computation to predict the users’ intentions and even to justify the reactive or proactive users’ behaviors.

Keywords

decision support system ambient intelligence speculative computation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Pinedo, M., Villanueva, F., Santofimia, M., López, J.: Multimodal Positioning Support for Ambient Intelligence. In: 5th International Symposium on Ubiquitous Computing and Ambient Intelligence, pp. 1–8 (2011)Google Scholar
  2. 2.
    Guerrero, L., Vasquez, F., Ochoa, S.: An Indoor Navigation System for the Visually Impaired. Sensors 12(6), 8236–8258 (2012)CrossRefGoogle Scholar
  3. 3.
    Shim, J., Warkentin, M., Courtney, J., Power, D., Sharda, R., Carlsson, C.: Past, present, and future of decision support technology. Decision Support Systems 33(2), 111–126 (2002)CrossRefGoogle Scholar
  4. 4.
    Preuveneers, D., Novais, P.: A survey of software engineering best practices for the development of smart applications in Ambient Intelligence. Journal of Ambient Intelligence and Smart Environments 4(3), 149–162 (2012)Google Scholar
  5. 5.
    Sadri, F.: Ambient intelligence: A survey. ACM Computing Surveys (CSUR) 43(4), no. 36, 36–66 (2011)Google Scholar
  6. 6.
    Ramos, C., Augusto, J., Shapiro, D.: Ambient Intelligence—the Next Step for Artificial Intelligence. IEEE Intelligent Systems 23, 15–18 (2008)CrossRefGoogle Scholar
  7. 7.
    Cook, D., Augusto, J., Jakkula, V.: Ambient Intelligence: applications in society and opportunities for AI. Pervasive and Mobile Computing 5(4), 277–298 (2009)CrossRefGoogle Scholar
  8. 8.
    Mao, W., Gratch, J.: A utility-based approach to intention recognition. In: AAMAS 2004 Workshop on Agent Tracking: Modelling Other Agents from Observations (2004)Google Scholar
  9. 9.
    Suzic, R., Svenson, P.: Capabilities-based plan recognition. In: 9th International Conference on Information Fusion, Florence, Italy, pp. 1–7 (2006)Google Scholar
  10. 10.
    Pereira, L., Anh, H.: Elder care via intention recognition and evolution prospection. In: 18th International Conference on Applications of Declarative Programming and Knowledge Managment (INAP 2009), Évora, Portugal (2009)Google Scholar
  11. 11.
    Roy, P., Bouchard, B., Bouzouane, A., Giroux, S.: A hybrid plan recognition model for Alzheimer’s patients: interleaved-erroneous dilemma. In: IEEE/WIC/ACM International Conference on Intelligent Agent Technology, California, USA, pp. 131–137 (2007)Google Scholar
  12. 12.
    Satoh, K., Inoue, K., Iwanuma, K., Sakama, C.: Speculative Computation by Abduction under Incomplete Communication Environments. In: ICMAS 2000, pp. 263–270 (2000)Google Scholar
  13. 13.
    Burton, F.: Speculative Computation, Parallelism and Functional Programming. IEEE Transactions on Computers c-34, 1190–1193 (1985)CrossRefGoogle Scholar
  14. 14.
    Mann, S., Huang, J., Janzen, R., Lo, R., Rampersad, V., Chen, A., Doha, T.: Blind navigation with a wearable range camera and vibrotactile helmet. In: Proceedings of the 19th ACM International Conference on Multimedia - MM 2011, USA, p. 1325 (2011)Google Scholar
  15. 15.
    Satoh, K., Yamamoto, K.: Speculative computation with multi-agent belief revision. In: International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 897–904. ACM Press, New York (2002)Google Scholar
  16. 16.
    Satoh, K.: Speculative computation and abduction for an autonomous agent. IEICE Transactions 88-D(9), 2031–2038 (2005)Google Scholar
  17. 17.
    Satoh, K.: Kiga-kiku computing and speculative computation. Awareness: Self-Awareness in Automic Systems (2012)Google Scholar
  18. 18.
    Sycara, K.: Multiagent Systems. AI Magazine 19(2), 79–92 (1998)Google Scholar
  19. 19.
    Garcia-Valverde, T., Serrano, E., Botia, J.: Combining the real worldwith simulations for a robust testing of ambient intelligence services. Artificial Intelligence Review, 1–24 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • João Fernandes
    • 1
  • João Laranjeira
    • 3
  • Paulo Novais
    • 1
  • Goreti Marreiros
    • 2
    • 4
  • José Neves
    • 1
  1. 1.University of MinhoBragaPortugal
  2. 2.Institute of EngineeringPolytechnic of PortoPortoPortugal
  3. 3.CCTC – Computer Science and Technology CenterPortoPortugal
  4. 4.GECAD – Knowledge Engineering and Decision Support GroupPortoPortugal

Personalised recommendations