Photonic system for real-time detection, discrimination, and quantification of microbes in air

Abstract

We report the results of the non-invasive photonic system AUM for remote detection and characterization of different pathogenic bacterial strains and mixtures. AUM applies the concepts of elastic light scattering, statistical mechanics, artificial intelligence, and machine learning to identify, classify and quantify various microbes in the scattering volume in real-time and, therefore, can become a potential tool in controlling and managing diseases caused by pathogenic microbes.