Water turbidity sensing using a smartphone

Hussain, Iftikar; Ahamad, Kamal Uddin

doi:10.1039/c6ra02483a

Cited by 85 publications

(42 citation statements)

References 19 publications

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“…Turbidity (formazin nephelometric unit, FNU) is a well-known and easily measurable proxy for suspended sediment concentration in sediment transport applications [54]. It here refers to a measurement of water clarity, indicating how intensively light is scattered by suspended particles within the water column [55]. The general, semi-analytical turbidity algorithm was calibrated for Landsat TM, ETM+, and OLI imagery using a wide range of field data from coastal and estuarine environments in Europe and South America, based on a switching algorithm of red and NIR RRS values [43].…”

Section: Landsat Turbidity Retrievalmentioning

confidence: 99%

Long-Term High-Resolution Sediment and Sea Surface Temperature Spatial Patterns in Arctic Nearshore Waters Retrieved Using 30-Year Landsat Archive Imagery

et al. 2019

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The Arctic is directly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems, the subsistence economy of the local population, and the climate because of the transformation of organic matter into greenhouse gases. Yet, the patterns of sediment dispersal in the nearshore zone are not well known, because ships do not often reach shallow waters and satellite remote sensing is traditionally focused on less dynamic environments. The goal of this study is to use the extensive Landsat archive to investigate sediment dispersal patterns specifically on an exemplary Arctic nearshore environment, where field measurements are often scarce. Multiple Landsat scenes were combined to calculate means of sediment dispersal and sea surface temperature under changing seasonal wind conditions in the nearshore zone of Herschel Island Qikiqtaruk in the western Canadian Arctic since 1982. We use observations in the Landsat red and thermal wavebands, as well as a recently published water turbidity algorithm to relate archive wind data to turbidity and sea surface temperature. We map the spatial patterns of turbidity and water temperature at high spatial resolution in order to resolve transport pathways of water and sediment at the water surface. Our results show that these pathways are clearly related to the prevailing wind conditions, being ESE and NW. During easterly wind conditions, both turbidity and water temperature are significantly higher in the nearshore area. The extent of the Mackenzie River plume and coastal erosion are the main explanatory variables for sediment dispersal and sea surface temperature distributions in the study area. During northwesterly wind conditions, the influence of the Mackenzie River plume is negligible. Our results highlight the potential of high spatial resolution Landsat imagery to detect small-scale hydrodynamic processes, but also show the need to specifically tune optical models for Arctic nearshore environments.

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Section: Landsat Turbidity Retrievalmentioning

confidence: 99%

Long-Term High-Resolution Sediment and Sea Surface Temperature Spatial Patterns in Arctic Nearshore Waters Retrieved Using 30-Year Landsat Archive Imagery

et al. 2019

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“…This can thus be used to detect particles based on size characteristics and to detect aggregation/agglutination within samples. Mie scattering has been recently applied for quantifying discrete particles in turbidity, 96 as well as for quantifying bacteria concentrations in water, meat, and urine samples. [97][98][99] While Rayleigh scattering also varies over the scattering angle, these changes are rather monotonic and may provide weaker signals for distinguishing particle size in aggregation/ agglutination-induced biosensing.…”

Section: Scattering-based Sensorsmentioning

confidence: 99%

Recent approaches for optical smartphone sensing in resource-limited settings: a brief review

2016

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“…The present sensing tool is based on light scattering principle, using which it is also possible to monitor the concentration of nonbiological and inorganic samples such as clay, sand particles, sulfate and chloride compounds generally present in various water bodies . The designed sensor is also suitable for estimation of turbidity level of drinking water.…”

Section: Resultsmentioning

confidence: 99%

Turbidimetric analysis of growth kinetics of bacteria in the laboratory environment using smartphone

Hatiboruah

Devi

Namsa

et al. 2020

Journal of Biophotonics

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For different microbiological and pathological studies, it is often required to monitor the growth of bacteria in a cultured medium in the laboratory environment. UV-VIS spectrophotometer is commonly used to estimate the growth of bacterial cell population by measuring the absorbance at 600 nm over a period of time. Colony-forming unit (CFU) is another approach, which has been routinely performed to estimate the live bacterial cells on semisolid agar plates. Herein, we demonstrate an alternative yet highly reliable sensing platform on a smartphone using which growth kinetics of different bacteria can be reliably monitored. The performance of the proposed smartphone sensor has been compared with the data obtained from OD600 and CFU analysis. A good correlation of bacterial growth rates enumerated based on the proposed smartphone sensor, bench-top spectrophotometer and CFU analysis have been observed under the experimental conditions. K E Y W O R D S bacteria, CFU Luria-broth medium, light scattering, optical density, smartphone

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Water turbidity sensing using a smartphone

Abstract: Smartphone based platform turbidimeter measuring turbidity in drinking and different environmental water bodies.

Cited by 85 publications

References 19 publications

Long-Term High-Resolution Sediment and Sea Surface Temperature Spatial Patterns in Arctic Nearshore Waters Retrieved Using 30-Year Landsat Archive Imagery

Long-Term High-Resolution Sediment and Sea Surface Temperature Spatial Patterns in Arctic Nearshore Waters Retrieved Using 30-Year Landsat Archive Imagery

Recent approaches for optical smartphone sensing in resource-limited settings: a brief review

Turbidimetric analysis of growth kinetics of bacteria in the laboratory environment using smartphone

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