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Testing a Drop of Liquid Using Smartphone LiDAR

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies 2022 26 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 50 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Justin Chan, Ananditha Raghunath, Kelly Michaelsen, Shyamnath Gollakota

Summary

Researchers developed the first system to determine fluid properties like viscosity using smartphone LiDAR sensors, providing an accessible and contactless method that works with just a single drop of liquid.

Models

We present the first system to determine fluid properties using the LiDAR sensors present on modern smartphones. Traditional methods of measuring properties like viscosity require expensive laboratory equipment or a relatively large amount of fluid. In contrast, our smartphone-based method is accessible, contactless and works with just a single drop of liquid. Our design works by targeting a coherent LiDAR beam from the phone onto the liquid. Using the phone's camera, we capture the characteristic laser speckle pattern that is formed by the interference of light reflecting from light-scattering particles. By correlating the fluctuations in speckle intensity over time, we can characterize the Brownian motion within the liquid which is correlated with its viscosity. The speckle pattern can be captured on a range of phone cameras and does not require external magnifiers. Our results show that we can distinguish between different fat contents as well as identify adulterated milk. Further, algorithms can classify between ten different liquids using the smartphone LiDAR speckle patterns. Finally, we conducted a clinical study with whole blood samples across 30 patients showing that our approach can distinguish between coagulated and uncoagulated blood using a single drop of blood.

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