Articles | Volume 9, issue 2
https://doi.org/10.5194/dwes-9-37-2016
https://doi.org/10.5194/dwes-9-37-2016
Research article
 | 
26 Sep 2016
Research article |  | 26 Sep 2016

Application of machine learning for real-time evaluation of salinity (or TDS) in drinking water using photonic sensors

Sandip Kumar Roy and Preeta Sharan

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Cited articles

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Deosarkar, S. D., Pandhare, V. V., and Kattekar, P. S.: Densities and Refractive Indices of Potassium Salt Solutions in Binary Mixture of Different Compositions, J. Engin., 2013, 368576, https://doi.org/10.1155/2013/368576, 2012.
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Short summary
About 20 % of the world population lives in areas without sufficient portable water; 97 % of the water on the earth is seawater. Understanding the level of salinity/TDS of seawater is a necessity. Currently, determination of salt content is by chemical analysis and is time-consuming. Our research is to develop a lab on chip optical sensor to measure the percentage of salinity in water. Even a small % of salinity change in water can be detected in real time by the sensor continuously with accuracy.