Abstract
The rapid spread of COVID-19 prompted many to take precautions to control the transmission of the virus. The most crucial of these is face coverings, such as face masks, as the virus is an airborne pathogen capable of transmission via respiratory droplets. While there are developments in smart mask technologies, they only provide passive protection through filtration and internal decontamination against the virus. This paper describes a new approach to smart mask technology that actively monitors for airborne pathogens using a PM sensor and reduces the wearer’s exposure to them by an active mitigation strategy. This strategy involves using a mist spray to increase the pathogen’s particle size, which reduces their ability to linger in the air. This system can be controlled wirelessly via a mobile application, which also displays the monitoring data. Deployment areas of this smart mask include classrooms, hospitals, and workspaces. Our experimental results demonstrate that increasing droplet sizes reduces the settling time for pathogens. Our future work includes a more precise detection of pathogens and improvements in deploying mitigation using fine-grained analysis about the aerosol and artificial intelligence.
Reiner Dizon-Paradis
Postdoctoral Research Associate
My research interests include machine learning applications in national security, hardware security and assurance, artificial intelligence of Things, and robotics.