Jurnal Engine: Energi, Manufaktur, dan Material
Vol 6, No 1 (2022)

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

Muchamad Malik (Unknown)

Article Info

Publish Date
30 Dec 2021

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.

Copyrights © 2022




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
Jurnal Engine: Energi, Manufaktur, dan Material
Website

Abbrev

Jurnal_ENGINE

Publisher

Universitas Proklamasi 45 Yogyakarta

Subject

Control & Systems Engineering Energy Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Description

Jurnal Engine: Energi, Manufaktur, dan Material is registered with ISSN 2579-7433 (online) on The Indonesian Institute of Sciences (LIPI). This journal is under publishment of the Mechanical Engineering Department, Universitas Proklamasi 45 Yogyakarta. It is a scientific journal focusing on Energy, ...