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3D Gas Distribution with and without Artificial Airflow: An Experimental Study with a Grid of Metal Oxide Semiconductor Gas Sensors
Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain; Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain. (Department of Electronic and Biomedical Engineering / Institute for Bioengineering of Catalonia (IBEC))
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0001-5061-5474
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-0217-9326
Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain; Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain. (Department of Electronic and Biomedical Engineering / Institute for Bioengineering of Catalonia (IBEC))ORCID iD: 0000-0003-2663-2965
2018 (English)In: Proceedings, E-ISSN 2504-3900, Vol. 2, no 13, article id 911Article in journal (Refereed) Published
Abstract [en]

Gas distribution modelling can provide potentially life-saving information when assessing the hazards of gaseous emissions and for localization of explosives, toxic or flammable chemicals. In this work, we deployed a three-dimensional (3D) grid of metal oxide semiconductor (MOX) gas sensors deployed in an office room, which allows for novel insights about the complex patterns of indoor gas dispersal. 12 independent experiments were carried out to better understand dispersion patters of a single gas source placed at different locations of the room, including variations in height, release rate and air flow profiles. This dataset is denser and richer than what is currently available, i.e., 2D datasets in wind tunnels. We make it publicly available to enable the community to develop, validate, and compare new approaches related to gas sensing in complex environments.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI, 2018. Vol. 2, no 13, article id 911
Keywords [en]
MOX, metal oxide, flow visualization, gas sensors, gas distribution mapping, sensor grid, 3D, gas source localization, indoor
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-71962DOI: 10.3390/proceedings2130911OAI: oai:DiVA.org:oru-71962DiVA, id: diva2:1284131
Projects
SmokeBot (EC H2020, 645101)Available from: 2019-01-31 Created: 2019-01-31 Last updated: 2019-02-01Bibliographically approved

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Hernandez Bennetts, VictorLilienthal, Achim

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Hernandez Bennetts, VictorLilienthal, AchimMarco, Santiago
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