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Open AccessArticle

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

Karlsruhe Institute of Technology (KIT), TECO/Pervasive Computing Systems, Karlsruhe 76131, Germany
Author to whom correspondence should be addressed.
Sensors 2019, 19(3), 749;
Received: 7 January 2019 / Revised: 6 February 2019 / Accepted: 7 February 2019 / Published: 12 February 2019
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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. View Full-Text
Keywords: mobile sensing; PM; ubiquitous computing; atmospheric dust; Particulate Matter; low-cost sensor mobile sensing; PM; ubiquitous computing; atmospheric dust; Particulate Matter; low-cost sensor
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Budde, M.; Leiner, S.; Köpke, M.; Riesterer, J.; Riedel, T.; Beigl, M. FeinPhone: Low-cost Smartphone Camera-based 2D Particulate Matter Sensor. Sensors 2019, 19, 749.

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