It is aimed to develop a different system than existing facial recognition systems by adding functionality to facial recognition systems used in many areas today. Recently, with the covid-19 pandemic, curfews and difficulties in controlling these bans have been taken into account and this system has been developed to reduce them. A study was carried out in which an email was sent to the authorized person or persons after the Covid-19 diagnosed person registered in the data set in the system was viewed by the camera when he went out on the street. In the designed software, face recognition is first performed using the Haar-Cascades classifier and then using the LBPH (Local Binary Patterns Histograms) method. This process occurs by tagging each pixel of the introduced Image by mapping it to other pixels around it. The result of this labeling is stored by converting it to a binary number system. He tries to recognize the face by comparing the images he receives from the camera in real time with this number. During the recognition process, if the person was previously registered in the data set, they are taken into the “red” color frame. If not registered, it is enclosed in a “green” colored frame. People with red frames recognized by the camera are notified to authorized persons by the time, date and identification information they are seen. Based on 90 frames, the study has a success rate of 84.5% and an error rate of 15.5%.