Photonic system for real-time detection, discrimination, and quantification of microbes in air - Tatavarti, Rao; Nadimpalli, Sridevi; Mangina, Gowtham Venkata Kumar; Kiran Machiraju, Naga; Pachiyappan, Arulmozhivarman; Hiremath, Shridhar; Jagannathan, Venkataseshan; Viswanathan, Pragasam (Frontiers in Physics, 2023)
We report the successful results from the recently developed non-invasive photonic system AUM - for real-time, remote detection, discrimination, and quantification of different pathogenic bacterial strains and mixtures of bacterial species in the air. The uniqueness and novelty of the AUM photonic system lie in its ability to innovatively apply the concepts of elastic light scattering, statistical mechanics, artificial intelligence, and machine learning to identify, classify and quantify various microbes present in the scattering volume in real-time; and therefore, can become a potential tool in the control and management of diseases caused by pathogenic microbes.