DETEKSI SUHU TUBUH DAN MASKER WAJAH DENGAN MLX90614, OPENCV, KERAS/TENSORFLOW, DAN DEEP LEARNING

Authors

DOI:

https://doi.org/10.30588/jeemm.v6i1.910

Keywords:

Raspbeery Pi, MLX90614, Deeplearning, OpenCV, Tensorflow, Covid-19, Image Processing

Abstract

Digital image processing technology combined with sensors is currently being used. This technology can help various needs such as education, industry and health. During the COVID-19 crisis, people are required to wear masks for protection. The public is also required to check their temperature regularly, which will have a significant health impact. This can reduce the risk of transmitting the Covid-19 virus. In this study, the author uses a WebCam camera and a temperature sensor MLX90614 as a tool to monitor the use of masks and measure body temperature. The author uses OpenCV for digital image processing and Tensorflow as a deep learning method for mask detection. The result of this study is that Tensorflow can detect wearing a mask with 99% accuracy. The MLX90614 sensor can measure body temperature with 99% accuracy at a reading distance of 5 cm to 10 cm.

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Published

2021-12-30

How to Cite

Malik, M. (2021). DETEKSI SUHU TUBUH DAN MASKER WAJAH DENGAN MLX90614, OPENCV, KERAS/TENSORFLOW, DAN DEEP LEARNING. Jurnal Engine: Energi, Manufaktur, Dan Material, 6(1), 19–25. https://doi.org/10.30588/jeemm.v6i1.910

Issue

Vol. 6 No. 1 (2022)

Section

Articles

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