ABSTRACT
The lack of an in-depth system for determining exposure to COVID-19 has left people with a need for an autonomous method of tracking/monitoring user habits and active COVID-19 cases. The COVID Risk Aversion System (CRS) was created to track users and how often they encounter these risks around them. This project currently uses Ontario as a testbed. The CRS system consists of two main components: an in-house server and user application. Using internal and external technologies, CRS logs how often users interact with other users who have the application and the locations they visit. A server was developed to store every location that each user encounters and then categorizes a quantified risk to that specific location based on multiple factors. Risk is determined by COVID-19 cases in the area, risk values of people at given locations, and regional per capita cases of COVID-19. The server alters area risk based on decreasing or increasing cases within a specific region. Every hour, the server checks Ontario's COVID-19 statistics and updates the database's values, and then recalculates the dynamic values for all locations stored in the system. The client-side application reports the user's location every 5 minutes and requests information on all users geographically close to that person using Vincenty's formula. Twice a day, the application updates the user's risk based on the interactions the user has had throughout the day. Users can also view a map of Ontario that displays regional risk and can check the risk of specific locations. CRS aims to be an effective method at reducing the user's exposure to COVID-19.
ABSTRACT
The lack of an in-depth system for determining exposure to COVID-19 has left people with a need for an autonomous method of tracking/monitoring user habits and active COVID-19 cases. The COVID Risk Aversion System (CRS) was created to track users and how often they encounter these risks around them. This project currently uses Ontario as a testbed. The CRS system consists of two main components: an in-house server and user application. Using internal and external technologies, CRS logs how often users interact with other users who have the application and the locations they visit. A server was developed to store every location that each user encounters and then categorizes a quantified risk to that specific location based on multiple factors. Risk is determined by COVID-19 cases in the area, risk values of people at given locations, and regional per capita cases of COVID-19. The server alters area risk based on decreasing or increasing cases within a specific region. Every hour, the server checks Ontario's COVID-19 statistics and updates the database's values, and then recalculates the dynamic values for all locations stored in the system. The client-side application reports the user's location every 5 minutes and requests information on all users geographically close to that person using Vincenty's formula. Twice a day, the application updates the user's risk based on the interactions the user has had throughout the day. Users can also view a map of Ontario that displays regional risk and can check the risk of specific locations. CRS aims to be an effective method at reducing the user's exposure to COVID-19. © 2022 IEEE.