Author:
Costanzo Sandra,Flores Alexandra
Abstract
In this chapter, a conceptual framework for assessing the probability of COVID-19 transmission is presented and discussed. The Wells-Riley probabilistic methodology for indoor environments is adopted, by integrating updated clinical data, thereby ensuring a reliable estimation of the probability of infection, through the model implementation on a specific Android platform. Notifications are sent to the user when detecting a high probability of infection and high carbon dioxide concentration levels. In addition, the Bluetooth signal is exploited to accurately determine the proximity between devices, thus facilitating the efficient enforcement of social distancing protocols among individuals. The effectiveness of the proposed model is validated through the application on different test scenarios.
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