Engineering safer spaces: Using CO2 sensors to monitor ventilation quality and mitigate the risk of indoor airborne transmission of viruses

Abstract

With the emergence of the SARS-CoV-2 virus, scientific communities have been prompted to update their understanding of airborne transmission of viruses. While several guidelines today focus on reducing the risk of infection through human contact with droplets, there is increasing evidence that aerosol transmission accounts for a substantial amount of cases. This project was inspired by the current COVID-19 pandemic; we used Raspberry Pi micro-controllers and sensors to measure CO2 concentrations as a proxy for human activity in spaces. The measurements were then used to estimate ventilation parameters and conduct a risk assessment based on probability models developed from the Wells-Riley equation. We showed that monitoring CO2 levels is a viable way to study and model the risk of airborne viral infection in different spatial geometries. Additionally, safety recommendations were made to reduce the risk of infection in these spaces.