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FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor

Precise, location-specific fine dust measurement is central for the assessment of urban air quality. Classic measurement approaches require dedicated hardware, of which professional equipment is still prohibitively expensive (>10k$) for dense measurements, and inexpensive sensors do not meet accu...

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Detalles Bibliográficos
Autores principales: Budde, Matthias, Leiner, Simon, Köpke, Marcel, Riesterer, Johannes, Riedel, Till, Beigl, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387415/
https://www.ncbi.nlm.nih.gov/pubmed/30759877
http://dx.doi.org/10.3390/s19030749
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author Budde, Matthias
Leiner, Simon
Köpke, Marcel
Riesterer, Johannes
Riedel, Till
Beigl, Michael
author_facet Budde, Matthias
Leiner, Simon
Köpke, Marcel
Riesterer, Johannes
Riedel, Till
Beigl, Michael
author_sort Budde, Matthias
collection PubMed
description Precise, location-specific fine dust measurement is central for the assessment of urban air quality. Classic measurement approaches require dedicated hardware, of which professional equipment is still prohibitively expensive (>10k$) for dense measurements, and inexpensive sensors do not meet accuracy demands. As a step towards filling this gap, we propose FeinPhone, a phone-based fine dust measurement system that uses camera and flashlight functions that are readily available on today’s off-the-shelf smart phones. We introduce a cost-effective passive hardware add-on together with a novel counting approach based on light-scattering particle sensors. Since our approach features a 2D sensor (the camera) instead of a single photodiode, we can employ it to capture the scatter traces from individual particles rather than just retaining a light intensity sum signal as in simple photometers. This is a more direct way of assessing the particle count, it is robust against side effects, e.g., from camera image compression, and enables gaining information on the size spectrum of the particles. Our proof-of-concept evaluation comparing several FeinPhone sensors with data from a high-quality APS/SMPS (Aerodynamic Particle Sizer/Scanning Mobility Particle Sizer) reference device at the World Calibration Center for Aerosol Physics shows that the collected data shows excellent correlation with the inhalable coarse fraction of fine dust particles (r > 0.9) and can successfully capture its levels under realistic conditions.
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spelling pubmed-63874152019-02-26 FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor Budde, Matthias Leiner, Simon Köpke, Marcel Riesterer, Johannes Riedel, Till Beigl, Michael Sensors (Basel) Article Precise, location-specific fine dust measurement is central for the assessment of urban air quality. Classic measurement approaches require dedicated hardware, of which professional equipment is still prohibitively expensive (>10k$) for dense measurements, and inexpensive sensors do not meet accuracy demands. As a step towards filling this gap, we propose FeinPhone, a phone-based fine dust measurement system that uses camera and flashlight functions that are readily available on today’s off-the-shelf smart phones. We introduce a cost-effective passive hardware add-on together with a novel counting approach based on light-scattering particle sensors. Since our approach features a 2D sensor (the camera) instead of a single photodiode, we can employ it to capture the scatter traces from individual particles rather than just retaining a light intensity sum signal as in simple photometers. This is a more direct way of assessing the particle count, it is robust against side effects, e.g., from camera image compression, and enables gaining information on the size spectrum of the particles. Our proof-of-concept evaluation comparing several FeinPhone sensors with data from a high-quality APS/SMPS (Aerodynamic Particle Sizer/Scanning Mobility Particle Sizer) reference device at the World Calibration Center for Aerosol Physics shows that the collected data shows excellent correlation with the inhalable coarse fraction of fine dust particles (r > 0.9) and can successfully capture its levels under realistic conditions. MDPI 2019-02-12 /pmc/articles/PMC6387415/ /pubmed/30759877 http://dx.doi.org/10.3390/s19030749 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. 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/).
spellingShingle Article
Budde, Matthias
Leiner, Simon
Köpke, Marcel
Riesterer, Johannes
Riedel, Till
Beigl, Michael
FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor
title FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor
title_full FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor
title_fullStr FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor
title_full_unstemmed FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor
title_short FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor
title_sort feinphone: low-cost smartphone camera-based 2d particulate matter sensor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387415/
https://www.ncbi.nlm.nih.gov/pubmed/30759877
http://dx.doi.org/10.3390/s19030749
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