A framework for real-time image detection of bioaerosols

Abstract

Abstract Starting from the elastic light scattering and the induced fluorescence emission from airborne particles and extending to the counting and differentiation of the associated signals, a framework is proposed to describe the detection of bioaerosols using an image sensor. For validation, monodisperse NaCl particles were generated to mimic abiotic particles, while monodisperse 1% mass riboflavin particles were generated to mimic biotic particles. By challenging a prototype sensor with these particles, the exposure time, particle speed, and signal-to-noise ratio were shown to be critical parameters for detection. Additionally, it was displayed that the induced fluorescence emission can be isolated from the elastic light scattering by using a well-selected long-pass filter. Furthermore, correlating the color of the captured signals to an induced fluorescence contribution was shown to be a potential avenue of differentiation between biotic and abiotic particles. It is predicted that this color differentiation method can distinguish between a near-continuous range of visible induced fluorescence emission wavelengths, giving the ability to distinguish individual fluorophores from one another using simple filtering and a single detector. This framework will be used to further optimize the image-based bioaerosol sensor evaluated here.