DEVELOPING REAL-TIME FACE MASK DETECTION WITH FACIAL TEMPERATURE MEASURE FOR COVID-19 INDOOR MONITORING SYSTEM

Ari Aharari, Jair Minoro Abe, Kazumi Nakamatsu
Author affiliations

Authors

  • Ari Aharari SOJO University
  • Jair Minoro Abe Graduate Program in Production Engineering, Paulista University
  • Kazumi Nakamatsu School of Human Science and Environment, University of Hyogo

DOI:

https://doi.org/10.15625/1813-9663/37/3/15962

Keywords:

Deep Learning, Face Mask Detection, COVID-19, Convolutional Neural Network (CNN), Facial Temperature Measure.

Abstract

The coronavirus (COVID-19) is the latest pandemic that hit human health in 2019. Wear a face mask in public areas to decrease the spread of the coronavirus. This work presents real-time face mask detection with facial temperature measures for the COVID-19 indoor monitoring system. Detecting people using ultrasonic sensors, face mask detection, and facial temperature measure using Grid-Eye Sensor are three modules applied in the proposed system. We also evaluated the proposed monitoring system in the real environment and confirmed the accuracy of 98.8% of mask detection.

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Published

26-09-2021

How to Cite

[1]
A. Aharari, J. M. Abe, and K. Nakamatsu, “DEVELOPING REAL-TIME FACE MASK DETECTION WITH FACIAL TEMPERATURE MEASURE FOR COVID-19 INDOOR MONITORING SYSTEM”, JCC, vol. 37, no. 3, p. 279–289, Sep. 2021.

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Section

SPECIAL ISSUE DEDICATED TO THE MEMORY OF PROFESSOR PHAN DINH DIEU - PART A

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