Affiliation:
1. GVP-SIRC & GVP College of Engineering
2. CASTLE Advanced Technologies and Systems
3. VIT University
Abstract
Abstract
This article reports the successful results from the recently developed non-invasive photonic system AUM - for real time, discrimination and quantification of different pathogenic bacterial strains, and mixtures of bacterial species in air. The uniqueness and novelty of the AUM photonic system, lies 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.
Publisher
Research Square Platform LLC
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