Chemical detection using the receptor density algorithm

James A. Hilder*, Nick D.L. Owens, Mark J. Neal, Peter J. Hickey, Stuart N. Cairns, David P.A. Kilgour, Jon Timmis, Andy M. Tyrrell

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (SciVal)

Abstract

This paper describes the application of the receptor density algorithm, an artificial immune system, as used to detect chemicals from data provided by various spectrometers. The system creates chemical signatures which are matched to a library of known chemicals, allowing the positive identification of hazardous substances. The performance of the system is tested against a publicly available mass-spectrometry dataset, against which it has previously been demonstrated as an effective anomaly detection algorithm. An autonomous chemical-detection device is then discussed, in which the algorithm is running on hardware embedded in a Pioneer robot carrying a portable chemical agent monitor.

Original languageEnglish
Article number6392458
Pages (from-to)1730-1741
Number of pages12
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
Volume42
Issue number6
DOIs
Publication statusPublished - Nov 2012

Keywords

  • hazardous materials
  • SPECTRA
  • NEURAL-NETWORKS
  • ION MOBILITY SPECTROMETRY
  • chemical sensors
  • Biological techniques
  • spectroscopy

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