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Article
Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources
Sensors
  • Xiang Gao
  • Levent Acar, Missouri University of Science and Technology
Abstract

This paper addresses the problem of mapping odor distribution derived from a chemical source using multi-sensor integration and reasoning system design. Odor localization is the problem of finding the source of an odor or other volatile chemical. Most localization methods require a mobile vehicle to follow an odor plume along its entire path, which is time consuming and may be especially difficult in a cluttered environment. To solve both of the above challenges, this paper proposes a novel algorithm that combines data from odor and anemometer sensors, and combine sensors' data at different positions. Initially, a multi-sensor integration method, together with the path of airflow was used to map the pattern of odor particle movement. Then, more sensors are introduced at specific regions to determine the probable location of the odor source. Finally, the results of odor source location simulation and a real experiment are presented.

Department(s)
Electrical and Computer Engineering
Keywords and Phrases
  • Algorithms,
  • Chemical detection,
  • Integration,
  • Cluttered environments,
  • Detection of chemicals,
  • Distribution maps,
  • Localization method,
  • Multi-sensor integrations,
  • Odor sources,
  • Sensor integration,
  • Volatile chemicals,
  • Electronic nose,
  • Odor distribution map,
  • Odor source detection,
  • Sensor integration
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2016 MDPI AG, All rights reserved.
Publication Date
7-1-2016
Publication Date
01 Jul 2016
Citation Information
Xiang Gao and Levent Acar. "Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources" Sensors Vol. 16 Iss. 7 (2016) ISSN: 1424-8220
Available at: http://works.bepress.com/levent-acar/28/