Cargando…
Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources
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...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970083/ https://www.ncbi.nlm.nih.gov/pubmed/27384568 http://dx.doi.org/10.3390/s16071034 |
_version_ | 1782445908072333312 |
---|---|
author | Gao, Xiang Acar, Levent |
author_facet | Gao, Xiang Acar, Levent |
author_sort | Gao, Xiang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4970083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-49700832016-08-04 Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources Gao, Xiang Acar, Levent Sensors (Basel) Article 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. MDPI 2016-07-04 /pmc/articles/PMC4970083/ /pubmed/27384568 http://dx.doi.org/10.3390/s16071034 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. https://creativecommons.org/licenses/by/4.0/This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Gao, Xiang Acar, Levent Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources |
title | Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources |
title_full | Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources |
title_fullStr | Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources |
title_full_unstemmed | Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources |
title_short | Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources |
title_sort | multi-sensor integration to map odor distribution for the detection of chemical sources |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970083/ https://www.ncbi.nlm.nih.gov/pubmed/27384568 http://dx.doi.org/10.3390/s16071034 |
work_keys_str_mv | AT gaoxiang multisensorintegrationtomapodordistributionforthedetectionofchemicalsources AT acarlevent multisensorintegrationtomapodordistributionforthedetectionofchemicalsources |