Real-time pollen monitoring using digital holography Article Swipe
YOU?
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· 2020
· Open Access
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· DOI: https://doi.org/10.5194/amt-13-1539-2020
We present the first validation of the Swisens Poleno, currently the only operational automatic pollen monitoring system based on digital holography. The device provides in-flight images of all coarse aerosols, and here we develop a two-step classification algorithm that uses these images to identify a range of pollen taxa. Deterministic criteria based on the shape of the particle are applied to initially distinguish between intact pollen grains and other coarse particulate matter. This first level of discrimination identifies pollen with an accuracy of 96 %. Thereafter, individual pollen taxa are recognized using supervised learning techniques. The algorithm is trained using data obtained by inserting known pollen types into the device, and out of eight pollen taxa six can be identified with an accuracy of above 90 %. In addition to the ability to correctly identify aerosols, an automatic pollen monitoring system needs to be able to correctly determine particle concentrations. To further verify the device, controlled chamber experiments using polystyrene latex beads were performed. This provided reference aerosols with traceable particle size and number concentrations in order to ensure particle size and sampling volume were correctly characterized.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5194/amt-13-1539-2020
- https://amt.copernicus.org/articles/13/1539/2020/amt-13-1539-2020.pdf
- OA Status
- gold
- Cited By
- 140
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2992239651
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2992239651Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5194/amt-13-1539-2020Digital Object Identifier
- Title
-
Real-time pollen monitoring using digital holographyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-03-31Full publication date if available
- Authors
-
Eric Sauvageat, Yanick Zeder, Kevin Auderset, Bertrand Calpini, Bernard Clot, Benoît Crouzy, Thomas Konzelmann, Gian-Duri Lieberherr, Fiona Tummon, Konstantina VasilatouList of authors in order
- Landing page
-
https://doi.org/10.5194/amt-13-1539-2020Publisher landing page
- PDF URL
-
https://amt.copernicus.org/articles/13/1539/2020/amt-13-1539-2020.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://amt.copernicus.org/articles/13/1539/2020/amt-13-1539-2020.pdfDirect OA link when available
- Concepts
-
Pollen, Particle (ecology), Computer science, Range (aeronautics), Aerobiology, Sampling (signal processing), Digital holography, Holography, Biological system, Environmental science, Remote sensing, Artificial intelligence, Computer vision, Geology, Materials science, Optics, Botany, Physics, Biology, Composite material, Oceanography, Filter (signal processing)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
140Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 18, 2024: 15, 2023: 33, 2022: 32, 2021: 31Per-year citation counts (last 5 years)
- References (count)
-
50Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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