Deteksi Wajah Bermasker Menggunakan Webcam dan AWS EC2 Berbasis Raspberry Pi - Maitsa Nabila; Rika Idmayanti; Indri Rahmayuni (SOTVI - Society of Visual Informatics, 2021)
In the COVID-19 pandemic, masks are an important necessity for the community. The use of masks is very important to prevent the transmission of COVID-19. During the current pandemic, the Padang State Polytechnic campus allows students to visit the library on the terms and conditions that students must comply with health protocols. However, there are still many students who do not comply with health protocols, especially in using masks. Therefore, a tool that can detect masks is needed to protect/prevent people who do not wear masks from wearing masks when visiting the library in order to prevent the spread of COVID-19. The face detection system is masked or not using python version 3 with the OpenCV library, and Tensorflow. This system uses a webcam, Raspberry Pi 3 Model B, and Buzzer. The webcam is used to capture the image of the mask user. The captured image will be processed and classified on the Raspberry Pi 3 Model B. A buzzer will sound if the classification result is a face without a mask. The tool will be equipped with displaying the results of monitoring library visitor data in the form of a website using AWS EC2 as the infrastructure