5.1. Smartphone Cleaning App
Cleaning activities play an important role in reducing the risk of being exposed to COVID-19. Three types of user activities were defined for the purposes of this research: Working (i.e., the user is busy working), not working (i.e., the user is either a visitor or having time off), and cleaning (i.e., the user is a staff member who is either cleaning or disinfecting the room). As seen in Figure 8a, these three different activities were taken into consideration by the mobile application and the user-selected types of activities were internally stored in their mobile phones.
We assumed that after the cleaning activity was carried out, the risk of any COVID-19 viral load being present returned to zero. Over time, interactions between users and the space such as coughing, talking, and touching surfaces would again increase each room’s risk (Equation (2)). If a cleaner specifies in the mobile app that cleaning is done, the room will be marked as “cleaned”, and the risk will go down to zero. Cleaning staff, based on the COVID-19 dissecting rules and regulations forced by the facilities, are trained and clean the room using advanced cleaning equipment (e.g., electrostatic sprayers), which kills 99% viruses. This cleaning activity ensures the virus is killed, and there is no chance for cross-contamination. It is reasonable to assume that the facilities will take precautions with cleaning as much as possible. However, if this assumption is not valid, the risk will be increased over time, which complicates the calculations and increases virus spread and true-positive alarms. Considering cleaning activities resets the risk calculations for the final risk map and reduces false-positive COVID-19 notification alerts. In the future, we are going to evaluate standard-level cleaning activities for COVID-19 using smart cameras automatically. Furthermore, cleaning should include enhanced space ventilation, as airborne particles are remarkably decreased by adequate ventilation.
For this research, a virus transmission interval is assumed to be a time interval of 15 min. In other words, if user A was interacting with a room that had been used by a positive COVID-19 infected person, user B, the system would notify user A of probable exposure to the virus. If we consider the situation in which cleaning activity took place after user B left the room, the risk of being exposed by the infected place would be zero. This case can be considered a false positive notification alert for user A. As a result, the proposed system can considerably reduce false positive notifications by using different types of activities. A demo scenario of cleaning person is presented in Supplementary Materials and the trajectories of both building cleaners and visitors is shown in Supplementary Materials.