A new system to detect coronavirus social distance violation - Marta Botella-Campos; José Luis Gacía-Navas; Albert Rego; Sandra Sendra; Jaime Lloret (International Journal of Electrical and Computer Engineering (IJECE), 2021)
In this paper, a novel solution to avoid new infections is presented. Instead of tracing users’ locations, the presence of individuals is detected by analysing the voices, and people’s faces are detected by the camera. To do this, two different Android applications were implemented. The first one uses the camera to detect people’s faces whenever the user answers or performs a phone call. Firebase Platform will be used to detect faces captured by the camera and determine its size and estimate their distance to the phone terminal. The second application uses voice biometrics to differentiate the users’ voice from unknown speakers and creates a neural network model based on 5 samples of the user’s voice. This feature will only be activated whenever the user is surfing the Internet or using other applications to prevent undesired contacts. Currently, the patient’s tracking is performed by geolocation or by using Bluetooth connection. Although face detection and voice recognition are existing methods, this paper aims to use them and integrate both in a single device. Our application cannot violate privacy since it does not save the data used to carry out the detection and does not associate this data to people.