SmartFluo: A Method and Affordable Adapter to Measure Chlorophyll a Fluorescence with Smartphones

Abstract

In order to increase the monitoring capabilities of inland and coastal waters, there is a need for new, affordable, sensitive and mobile instruments that could be operated semi-automatically in the field. This paper presents a prototype device to measure chlorophyll a fluorescence: the SmartFluo. The device is a combination of a smartphone offering an intuitive operation interface and an adapter implying a cuvette holder, as well as a suitable illumination source. SmartFluo is based on stimulated fluorescence of water constituents such as chlorophyll a. The red band of the digital smartphone camera is sensitive enough to detect quantitatively the characteristic red fluorescence emission. The adapter contains a light source, a strong light emitting diode and additional filters to enhance the signal-to-noise ratio and to suppress the impact of scattering. A novel algorithm utilizing the red band of the camera is provided. Laboratory experiments of the SmartFluo show a linear correlation (R2 = 0.98) to the chlorophyll a concentrations measured by reference instruments, such as a high-performance benchtop laboratory fluorometer (LS 55, PerkinElmer).

Estimation of Reservoir Bio-Optical Water Quality Parameters Using Smartphone Sensor Apps and Landsat ETM+: Review and Comparative Experimental Results

“…Busch et al [32,33] also compared ocean colour satellite measurements with the Eye-OnWater app local colour observations, with in situ laboratory and field tests in the determination of the water colour, transparency, chlorophyll-a fluorescence, and phytoplankton dynamics, respectively. Their results showed accuracies of more than 90% and also demonstrated the effectiveness of colour-based low-cost sensors for citizen-based contributions in filling observational gaps and increasing environmental stewardship among the public in monitoring their environments [28,32,34].…”

“…They reported a significant correlation between the spectral index from Landsat OLI imagery and Chl-a in Jordan Lake, for different months of the year. Further, [28] recently used the SmartFluo app, which is based on stimulated fluorescence of water constituents, to measure the fluorescence of chlorophyll-a. In comparison with the laboratory experiments, SmartFluo showed a linear correlation of R 2 = 0 98 to the chlorophyll-a concentrations as measured using a benchtop laboratory fluorometer (LS 55, PerkinElmer).…”

“…In general, the results from this study may not be as strong due to the unique reservoir morphology and water composition, which can be attributed to the reservoir system turnover effect, when the equalization of the thermal gradient in the reservoir induces mixing of surface and bottom waters, making remote monitoring difficult due to instability [60]. However, the main contribution of this research is that the automated processing methodology allowed for the processing and analysis of selected physical water quality parameters using the in situ laboratory assessments, and radiance analysis of Landsat ETM+ and smartphone camera 25 Journal of Sensors observations, with significant potential for rapid water quality analysis, and for the involvement and encouragement of citizens to participate in environmental resource monitoring, such as water quality assessments and reporting using stateof-the art techniques including smartphone apps and satellite data [28,[32][33][34].…”

Expanding Aquatic Observations through Recreation

“…Sensor developments for monitoring nutrient concentrations (Beaton et al, 2011) and toxic pollutants (Lafleur et al, 2010) may one day be feasible from such platforms. New manufacturing techniques, including 3D printers (Mohammed, 2016), small low cost electronics (Leeuw et al, 2013) 5 , embedded computing (Williams et al, 2014) 6 and mobile phones (Friedrichs et al, 2017) are expanding possibilities further. With growing developments in wireless sensor networks (Albaladejo et al, 2010), cloud data storage, and visualization (Müller et al, 2016), the feasibility of harnessing recreational sports for aquatic monitoring is increasing.…”

Citizen observations contributing to flood modelling: opportunities and challenges

“…Citizen Observatories have been researched in several EU-funded projects. Finished projects (CITI-SENSE, Citclops, COBWEB, OMNISCIENTIS and WeSenseIt) already resulted in valuable contributions to the field Aspuru et al, 2016;Friedrichs et al, 2014;Higgins et al, 2016;Uhrner et al, 2013). The currently running CO projects (Ground Truth 2.0, LANDSENSE, SCENT and GROW Observatory) propose to investigate this concept further.…”