Skip to main content

Advertisement

Springer Nature Link
Log in

An adaptive sensor network for home intrusion detection by human activity profiling

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

An adaptive sensor network for home intrusion detection is proposed. The sensor network combines profile-based anomaly detection and adaptive information processing based on hidden Markov models (HMM) that allow the system to train and tune the profiles automatically. The trade-off between miss-alarms and false alarms has been studied experimentally. Several types of hypothetical intrusion have been tested and successfully detected. However, hypothetical anomalies such as supposing that a resident has fallen down due to sudden illness have been difficult to detect.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Culler DE, Mulder H (2004) Smart sensors to network the world. Sci Am, June

  2. Culler DE, Estrin D, Srivastava M (2004) Overview of sensor networks. Special Issue in Sensor Networks, IEEE Computer 37(8):41–49

    Google Scholar 

  3. Ishida Y (2004) Immunity-based systems: a design perspective. Springer

  4. Rabiner LR (1990) A tutorial on hidden Markov models and selected applications in speech recognition. In: Readings in speech recognition. Morgan Kaufmann, Los Altos, CA, pp 267–296

    Google Scholar 

  5. Preece SJ, Goulermas JY, Kenney LPJ, et al (2009) Activity identification using body-mounted sensors: a review of classification techniques. Physiol Measure 30(4):R1–R33

    Article  Google Scholar 

  6. Yin J, Yang Q, Pan JJ (2008) Sensor-based abnormal human activity detection. IEEE Trans Knowledge Data Eng 20(8):1082–1090

    Article  Google Scholar 

  7. Wilson AD, Bobick AF (1999) Parametric hidden Markov models for gesture recognition. IEEE Trans Pattern Anal Mach Intell 21(9):884–900

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Information Engineering, Toyohashi University of Technology, Tempaku, Toyohashi, Aichi, 441-8580, Japan

    Masahiro Tokumitsu, Masashi Murakami & Yoshiteru Ishida

Authors
  1. Masahiro Tokumitsu
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Masashi Murakami
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Yoshiteru Ishida
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Yoshiteru Ishida.

Additional information

This work was presented in part at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010

About this article

Cite this article

Tokumitsu, M., Murakami, M. & Ishida, Y. An adaptive sensor network for home intrusion detection by human activity profiling. Artif Life Robotics 16, 36–39 (2011). https://doi.org/10.1007/s10015-011-0872-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-011-0872-5

Key words