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

Budde, Matthias; Leiner, Simone; Köpke, Marcel; Riesterer, Johannes; Riedel, Till; Beigl, Michael

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 sever ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000090936
Veröffentlicht am 13.02.2019
Seitenaufrufe: 43
seit 14.02.2019
Downloads: 8
seit 17.02.2019
Zugehörige Institution(en) am KIT Institut für Telematik (TM)
Institut für Experimentelle Teilchenphysik (ETP)
Publikationstyp Zeitschriftenaufsatz
Jahr 2019
Sprache Englisch
Identifikator ISSN: 1424-8220
KITopen-ID: 1000090936
Erschienen in Sensors
Band 19
Heft 3
Seiten Article: 749
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Schlagworte mobile sensing; PM; ubiquitous computing; atmospheric dust; Particulate Matter; low-cost sensor
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