Comparison of Face Masks by Arduino Sensors
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Keywords

Face Masks
COVID-19
Arduino Sensors

How to Cite

Balkir, B., Lankar, V., & Hangun, Y. (2023). Comparison of Face Masks by Arduino Sensors. Cornell Undergraduate Research Journal, 2(2), 63–73. https://doi.org/10.37513/curj.v2i2.733

Abstract

The COVID-19 pandemic in early 2020 has created a health crisis around the world. There have been many precautions taken against the virus, such as social distancing and the use of personal protective equipment. Face masks are an essential part of personal protective equipment, especially for essential workers. Although the pandemic has caused a high demand for facemasks, there is limited scientific knowledge available on the various types of masks. Knowledge about the air quality inside the different facemasks could be beneficial for both the COVID-19 pandemic and future disease outbreaks, which will seemingly increase in the future. There are different types of masks, ranging from tight-fitting N95 respirator masks to looser surgical masks to homemade cloth masks. Herein, N95 respirator masks, surgical masks, cloth face masks, and surgical masks on top of N95 respirator masks were compared in terms of CO2 levels, Volatile Organic Compound levels (VOCs), temperature, humidity, and O2 concentrations. To record these measurements, Arduino-based sensors were constructed and utilized for the measurements. It was found that the N95 mask and the surgical mask on top of the N95 mask trapped the highest concentration of carbon dioxide, VOCs, temperature, humidity, and the lowest oxygen levels compared to the surgical mask and cloth mask.

https://doi.org/10.37513/curj.v2i2.733
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Copyright (c) 2023 Berk Balkir