LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Gardner, J. W.; Taylor, J. E. (2009)
Publisher: Institute of Electrical and Electronic Engineers
Languages: English
Types: Article
Subjects: TK
As our understanding of the human olfactory system has grown, so has our ability to design artificial devices that mimic its functionality, so called electronic noses (e-noses). This has led to the development of a more sophisticated biomimetic system known as an artificial olfactory mucosa (e-mucosa) that comprises a large distributed sensor array and artificial mucous layer. In order to exploit fully this new architecture, new approaches are required to analyzing the rich data sets that it generates. In this paper, we propose a novel convolution based approach to processing signals from the e-mucosa. Computer simulations are performed to investigate the robustness of this approach when subjected to different real-world problems, such as sensor drift and noise. Our results demonstrate a promising ability to classify odors from poor sensor signals.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] J. W. Gardner and P. N. Bartlett, Electronic Noses: Principles and Applications. Oxford, U.K.: Oxford Univ. Press, 1999.
    • [2] M. A. Ryan et al., “Monitoring space shuttle air quality using the jet propulsion laboratory electronic nose,” IEEE Sensors J., vol. 4, no. 3, pp. 337-347, Jun. 2004.
    • [3] R. C. Young, W. J. Buttner, B. R. Linnell, and R. Ramesham, “Electronic nose for space program applications,” Sens. Actuators B, vol. 93, pp. 7-16, 2003.
    • [4] M. M. Mozell and M. Jagodowicz, “Chromatographic separation of odorants by the nose: Retention times measured across in vivo olfactory mucosa,” Science, vol. 181, pp. 1247-1249, 1973.
    • [5] P. Vroon, Smell: The Secret Seducer. New York: Strauss and Giroux, 1997, p. 28.
    • [6] S. L. Tan, “Smart Chemical Sensing: Towards a Nose-on-a-Chip,” Ph.D. dissertation, Univ. Warwick, School of Engineering, Coventry, U.K., 2005.
    • [7] R. Gutiérrez-Osuna, “Pattern analysis for machine olfaction: A review,” IEEE Sensors J., vol. 2, no. 3, pp. 189-201, Jun. 2002.
    • [8] A. Perera, T. Yamanaka, A. Gutiérrez-Gálvez, B. Raman, and R. Gutiérrez-Osuna, “A dimensionality-reduction technique inspired by receptor convergence in the olfactory system,” Sens. Actuators B, vol. 116, pp. 17-22, 2006.
    • [9] M. Bicego, G. Tessari, G. Tecchiolli, and M. Bettinelli, “A comparative analysis of basic pattern recognition techniques for the development of small size electronic nose,” Sens. Actuators B, vol. 85, pp. 137-144, 2002.
    • [10] I. I. Hirschman and D. V. Widdler, The Convolution Transform. Princeton, NJ: Princeton Univ. Press, 1955.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article