An Optical Scattering Based Cost-Effective Approach Towards Quantitative Assessment Of Turbidity And Particle Size Estimation In Drinking Water Using Image Analysis

Soumendra Singh, Animesh Halder, Amrita Banerjee, Nur Hasan, Arpan Bera, Oindrila Sinha, Sanjay K. Ghosh, Amitabha Mitra and Samir Pal

No davfq, EcoEvoRxiv from Center for Open Science

Abstract: Contaminated water consumption primarily for drinking purposes is the cause of approximately 502,000 global deaths every year mostly in economically challenging countries indicating the need for a cheap, easy to use a yet robust and scientifically proven method for determination of water quality. In this work, we have characterized the water quality utilizing the principles of optical scattering by the suspended particulate matter using a low-cost wireless-enabled camera. The images grabbed by the camera on an optically lit cast screen on a red and a blue dot were allowed to arrive through a “model scattering medium". An estimate of the amount of light reaching the detector camera essentially provide Optical Density of the medium. Edge blurring of the captured images reveals information of the suspended particulates (sizes) in the medium. The individual pixel information was analyzed and the 'edge blurring' phenomenon was shown on an RGB intensity curve. The average diameter of the dominant suspended particles presents in the model scattering medium is also estimated from the fitting parameters and compared with that from commercially available Dynamic Light Scattering (DLS) instrument. The system is effective in measuring bacterial growth and the acquired data have been compared with that of the growth curve obtained from the gold standard method. Limit of Detection (LOD) of the set-up was found to be 48 ppm. The extremely cost-effective nature of the set-up, the innovative method of analysis, and easy availability of components would expectedly make water quality assessment very easy and user friendly.

Date: 2020-09-23
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Persistent link: https://EconPapers.repec.org/RePEc:osf:ecoevo:davfq

DOI: 10.31219/osf.io/davfq

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