Skip to main content

Abstract

Cognitive impaired population face with innumerable problems in their daily life. Surprisingly, they are not provided with any help to perform those tasks for which they have difficulties. As a consequence, it is necessary to develop systems that allow those people to live independently and autonomously. Living in a technological era, people could take advantage of the available technology, being provided with some solutions to their needs. This paper presents a platform that assists users with remembering where their possessions are. Mainly, an object recognition process together with an intelligent scheduling applications are integrated in an Ambient Assisted Living (AAL) environment.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Acampora, G., Loia, V.: A dynamical cognitive multi-agent system for enhancing ambient intelligence scenarios. In: IEEE Int. Conf. on Fuzzy Systems, pp. 770–777 (2009)

    Google Scholar 

  2. Ahmed, S., El-Sayed, K., Elhabian, S.: Moving object detection in spatial domain using background removal techniques - state-of-art. Recent Patents on Computer Sciencee 1(1), 32–54 (2008)

    Article  Google Scholar 

  3. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (surf). CVIU 110(3), 346–359 (2008)

    Google Scholar 

  4. Bileschi, S.M., Wolf, L.: A unified system for object detection, texture recognition, and context analysis based on the standard model feature set. In: British Machine Vision Conference, vol. 83, pp. 1–10 (2005)

    Google Scholar 

  5. Borotschnig, H., Paletta, L., Prantl, M., Pinz, A.: Appearance-based active object recognition. Image and Vision Computing 18(9), 715–727 (2000)

    Article  Google Scholar 

  6. Ciliberto, C., Pattacini, U., Natale, L., Nori, F., Metta, G.: Reexamining lucas-kanade method for real-time independent motion detection: Application to the icub humanoid robot. In: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 4154–4160 (2011)

    Google Scholar 

  7. Costa, A., Castillo, J.C., Novais, P., Fernández-Caballero, A., Simoes, R.: Sensor-driven agenda for intelligent home care of the elderly. Expert Systems with Applications 39(15), 12,192–12,204 (2012), doi:10.1016/j.eswa, 04.058

    Google Scholar 

  8. Costa, A., Novais, P., Corchado, J.M., Neves, J.: Increased performance and better patient attendance in an hospital with the use of smart agendas. Logic Journal of IGPL 20(4), 689–698 (2012), doi:10.1093/jigpal/jzr021

    Google Scholar 

  9. Cristinacce, D., Cootes, T.F.: Boosted regression active shape models. In: British Machine Vision Conference, vol. 2, pp. 880–889 (2007)

    Google Scholar 

  10. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR, vol. 1, pp. 886–893 (2005)

    Google Scholar 

  11. Guido, D.: AP Neuroscience Course (2011), http://www.rhsmpsychology.com/

  12. Keysers, D., Deselaers, T., Breuel, T.M.: Optimal geometric matching for patch-based object detection. ELCVIA 6(1), 44–54 (2007)

    Google Scholar 

  13. Marques, V., Costa, A., Novais, P.: A dynamic user profiling technique in a AmI environment. In: World Congress on Information and Communication Technologies, pp. 1247–1252. IEEE (2011), doi:10.1109/WICT.2011.6141427

    Google Scholar 

  14. Martinez-Martin, E., del Pobil, A.P.: Robust Motion Detection in Real-Life Scenarios, springerbr edn. Springer Briefs in Computer Science. Springer, London (2012), doi:10.1007/978-1-4471-4216-4

    Book  Google Scholar 

  15. Martínez-Martín, E., del Pobil, A.P.: Robust object recognition in an unstructured environment. In: Lee, S., Cho, H., Yoon, K.-J., Lee, J. (eds.) Intelligent Autonomous Systems 12. AISC, vol. 193, pp. 705–714. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  16. Migliore, D.A., Matteucci, M., Naccari, M.: A revaluation of frame difference in fast and robust motion detection. In: 4th ACM Int. Workshop on Video Surveillance and Sensor Networks - VSSN 2006, p. 215. ACM Press, New York (2006)

    Google Scholar 

  17. Radde, S., Freitag, B.: Using Bayesian Networks To Infer Product Rankings From User Needs. In: UMAP 2010 Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (2010)

    Google Scholar 

  18. Serre, T., Wolf, L., Poggio, T.: Object recognition with features inspired by visual cortex. In: CVPR, vol. 2, pp. 994–1000 (2005)

    Google Scholar 

  19. Shahbaz Khan, F., Anwer, R.M., van de Weijer, J., Bagdanov, A.D., Vanrell, M., Lopez, A.M.: Color attributes for object detection. In: CVPR, pp. 3306–3313 (2012)

    Google Scholar 

  20. Tazari, M.R., Wichert, R., Norgall, T.: Towards a unified ambient assisted living and personal health environment. In: Wichert, R., Eberhardt, B. (eds.) Ambient Assisted Living, vol. 63, pp. 141–155. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  21. Toshev, A., Taskar, B., Daniilidis, K.: Shape-based object detection via boundary structure segmentation. IJCV 99(2), 123–146 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  22. Ughetti, M., Trucco, T., Gotta, D.: Development of agent-based, peer-to-peer mobile applications on android with jade. In: The 2nd Int. Conf. on Mobile Ubiquitous Computing, Systems, Services and Technologies, pp. 287–294 (2008)

    Google Scholar 

  23. Urdiales, C., Dominguez, M., de Trazegnies, C., Sandoval, F.: A new pyramid-based color image representation for visual localization. Image and Vision Computing 28(1), 78–91 (2010)

    Article  Google Scholar 

  24. Urtasun, R., Fleet, D.J., Fua, P.: Temporal motion models for monocular and multiview 3d human body tracking. CVIU 104(2-3), 157–177 (2006)

    Google Scholar 

  25. Varcheie, P.D.Z., Sills-Lavoie, M., Bilodeau, G.A.: An efficient region-based background subtraction technique. In: Canadian Conference on Computer and Robot Vision, pp. 71–78 (2008)

    Google Scholar 

  26. Vardasca, R., Simoes, R.: Needs and opportunities in ambient assisted living in portugal. In: 2nd Int. Living Usability Lab Workshop on AAL Latest Solutions, Trends and Applications, AAL 2012, in Conjunction with BIOSTEC 2012, pp. 100–108 (2012)

    Google Scholar 

  27. Watson, I.: An introduction to case-based reasoning. In: Watson, I.D. (ed.) UK CBR 1995. LNCS, vol. 1020, pp. 1–16. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ângelo Costa .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Costa, Â., Martinez-Martin, E., del Pobil, A.P., Simoes, R., Novais, P. (2013). Find It – An Assistant Home Agent. In: Pérez, J., et al. Trends in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent Systems and Computing, vol 221. Springer, Cham. https://doi.org/10.1007/978-3-319-00563-8_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00563-8_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00562-1

  • Online ISBN: 978-3-319-00563-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics