Pendeteksi Penggunaan Masker Wajah dengan ESP32Cam Menggunakan OpenCV dan Tensorflow

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Majalah Ilmiah Teknologi Elektro
Vol 21 No 2 (2022): (Juli - Desember) Majalah Ilmiah Teknologi Elektro

The government's recommendation to wear masks daily is very important to avoid the Covid-19. This article analyzes the use of the ESP32 Cam as a mask detector, where proper use must cover the nose and mouth. The captured images can be retrieved and executed by a program created using Python. The OpenCV library is used to access the camera, while the TensorFlow library with training files in the datasheet performs mask detection. The experimental results of detecting masks in bright conditions show the fastest time is 1 second with an ideal distance of 1m and a maximum distance of 2.5m. On the other hand, in dark conditions, the fastest time is 2 seconds with an ideal distance of 1m and a maximum distance of 1.5m.