dc.contributor.author | Drix, Damien | |
dc.contributor.author | Schmuker, Michael | |
dc.date.accessioned | 2021-02-05T14:14:36Z | |
dc.date.available | 2021-02-05T14:14:36Z | |
dc.date.issued | 2021-03-26 | |
dc.identifier.citation | Drix , D & Schmuker , M 2021 , ' Resolving Fast Gas Transients with Metal Oxide Sensors ' , ACS Sensors , vol. 6 , no. 3 , pp. 688-692 . https://doi.org/10.1021/acssensors.0c02006 | |
dc.identifier.issn | 2379-3694 | |
dc.identifier.uri | http://hdl.handle.net/2299/23850 | |
dc.description | © 2021 American Chemical Society. This is an Open Access article. https://creativecommons.org/licenses/by/4.0/ | |
dc.description.abstract | Electronic olfaction can help detect and localize harmful gases and pollutants, but the turbulence of the natural environment presents a particular challenge: Odor encounters are intermittent, and an effective electronic nose must therefore be able to resolve short odor pulses. The slow responses of the widely used metal oxide (MOX) gas sensors complicate the task. Here, we combine high-resolution data acquisition with a processing method based on Kalman filtering and absolute-deadband sampling to extract fast onset events. We find that our system can resolve the onset time of odor encounters with enough precision for source direction estimation with a pair of MOX sensors in a stereo-osmic configuration. | en |
dc.format.extent | 5 | |
dc.format.extent | 1513609 | |
dc.language.iso | eng | |
dc.relation.ispartof | ACS Sensors | |
dc.subject | Accelerated gas sensing | |
dc.subject | Event-based sampling | |
dc.subject | Kalman filter | |
dc.subject | Metal oxide sensors | |
dc.subject | Neuromorphic | |
dc.subject | Bioengineering | |
dc.subject | Instrumentation | |
dc.subject | Process Chemistry and Technology | |
dc.subject | Fluid Flow and Transfer Processes | |
dc.title | Resolving Fast Gas Transients with Metal Oxide Sensors | en |
dc.contributor.institution | Centre of Data Innovation Research | |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | Department of Computer Science | |
dc.contributor.institution | Biocomputation Research Group | |
dc.description.status | Peer reviewed | |
dc.identifier.url | http://www.scopus.com/inward/record.url?scp=85101022894&partnerID=8YFLogxK | |
rioxxterms.versionofrecord | 10.1021/acssensors.0c02006 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |