Skip to main content

Trace of Objects to Retrieve Prediction Patterns of Activities in Smart Homes

  • Conference paper
Conceptual Structures for Discovering Knowledge (ICCS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6828))

Included in the following conference series:

Abstract

An elderly person can forget sometimes to complete the activities that he begins. By the tracing of objects that he may apply in realization of activities in a smart home, it would be possible to predict his intention about what activity he considers to realize. In this way, we would be able to provide hypotheses about the Smart Home resident’s goals and his possible goal achievement’s defects. To achieve that, spatiotemporal aspects of daily activities are surveyed to mine the patterns of activities realized by the smart homes residents. Based on the inferred daily activities realization patterns we are able to make prediction patterns that can predict uncompleted activities.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Amirjavid, F., Bouzouane, A., Bouchard, B.: Action recognition under uncertainty in smart homes. In: MAICS (2011)

    Google Scholar 

  2. Zadeh, L.A.: Probability measures of fuzzy events. Journal Math. Anal. Appl. 23, 421–427 (1968)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bouchard, B., Bouzouane, A., Giroux, S.: A Keyhole Plan Recognition Model for Alzheimer’s Patients: First Results. Journal of Applied Artificial Intelligence (AAI) 22(7), 623–658 (2007)

    Article  Google Scholar 

  4. Jakkula, V., Cook, J.: Temporal pattern discovery for anomaly detection in a smart home. In: 3rd IET International Conference on Intelligent Environments, IE 2007 (2007)

    Google Scholar 

  5. Galushka, M., Patterson, D., Rooney, N.: Temporal data mining for smart homes (2007)

    Google Scholar 

  6. Mitsa, T.: Temporal data mining. Chapman and Hall/CRC (2010)

    Google Scholar 

  7. Ross Quinlan, J., Ghosh, J.: Top 10 Algorithms in Data Mining. In: IEEE international Conference on Data Mining, ICDM (December 2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Amirjavid, F., Bouzouane, A., Bouchard, B. (2011). Trace of Objects to Retrieve Prediction Patterns of Activities in Smart Homes. In: Andrews, S., Polovina, S., Hill, R., Akhgar, B. (eds) Conceptual Structures for Discovering Knowledge. ICCS 2011. Lecture Notes in Computer Science(), vol 6828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22688-5_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-22688-5_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22687-8

  • Online ISBN: 978-3-642-22688-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics