Sensors 2016, 16(10), 1649; https://doi.org/10.3390/s16101649
Ultraviolet Imaging with Low Cost Smartphone Sensors: Development and Application of a Raspberry Pi-Based UV Camera
Thomas C. Wilkes 1,*
, Andrew J. S. McGonigle 1,2, Tom D. Pering 1, Angus J. Taggart 1, Benjamin S. White 3, Robert G. Bryant 1 and Jon R. Willmott 3
, Andrew J. S. McGonigle 1,2, Tom D. Pering 1, Angus J. Taggart 1, Benjamin S. White 3, Robert G. Bryant 1 and Jon R. Willmott 3
1
Department of Geography, The University of Sheffield, Winter Street, Sheffield, S10 2TN, UK
2
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Palermo, via Ugo La Malfa 153, 90146 Palermo, Italy
3
Department of Electronic and Electrical Engineering, The University of Sheffield, Portobello Centre, Pitt Street, Sheffield, S1 4ET, UK
*
Author to whom correspondence should be addressed.
Received: 5 September 2016 / Accepted: 3 October 2016 / Published: 6 October 2016
(This article belongs to the Special Issue Imaging: Sensors and Technologies)
Abstract
Here, we report, for what we believe to be the first time, on the modification of a low cost sensor, designed for the smartphone camera market, to develop an ultraviolet (UV) camera system. This was achieved via adaptation of Raspberry Pi cameras, which are based on back-illuminated complementary metal-oxide semiconductor (CMOS) sensors, and we demonstrated the utility of these devices for applications at wavelengths as low as 310 nm, by remotely sensing power station smokestack emissions in this spectral region. Given the very low cost of these units, ≈ USD 25, they are suitable for widespread proliferation in a variety of UV imaging applications, e.g., in atmospheric science, volcanology, forensics and surface smoothness measurements. View Full-TextKeywords:
UV camera; UV imaging; smartphone sensor technology; sulphur dioxide emissions; Raspberry Pi; low-cost camera
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Wilkes, T.C.; McGonigle, A.J.S.; Pering, T.D.; Taggart, A.J.; White, B.S.; Bryant, R.G.; Willmott, J.R. Ultraviolet Imaging with Low Cost Smartphone Sensors: Development and Application of a Raspberry Pi-Based UV Camera. Sensors 2016, 16, 1649.
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