Air quality monitoring is critical for environmental health and public safety. Traditional monitoring methods rely on passive and active air sampling techniques, which, while effective, are cumbersome, expensive and limited with respect to real-time data and comprehensive analyses. In high-risk environments, such as hospital or care settings, and food processing/production facilities, where microbial contaminants can pose a threat, these limitations are more pronounced.
Researchers at Arizona State University have developed a microbial air quality monitoring system for enhanced detection and analysis of airborne microbial contaminants utilizing a novel combination of modern sensor technology, including CO2, NH3, VOC, particulate, temperature and humidity, with advanced software components. This system uses embedded machine learning running on microcontrollers to enable real-time microbial risk assessment directly on the device without relying on cloud infrastructure.
Additionally, in the event of future pandemics like COVID-19, this technology can help avoid full-scale economic shutdowns by providing real-time assessments of microbial and indirect viral risk levels in indoor environments. Businesses, schools, and public facilities could use MAQMS to monitor whether their air quality remains within safe thresholds. This enables data-informed decisions about closures or continued operation, potentially saving billions in economic losses and helping maintain public safety. Facilities that follow strong sanitation protocols could remain operational, preserving livelihoods and protecting vulnerable communities.
This technology fills a critical gap in existing microbial air quality monitoring which combines affordability with high performance and accessibility.
Potential Applications
Benefits and Advantages