Smart Early Screening System for COVID-19 Spreading Prevention

10 pages•Published: September 20, 2022

Abstract

Since the end of 2019, a respiratory disease called COVID-19 caused by SARS- COV2 has been spread around the world. The disease has similar symptoms with influenza. The common symptoms are cough, fever and fatigue. The human-to human transmission occurs primarily through droplets spread by coughing or sneezing from infected people directly and indirectly. In this paper a system based on embedded devices that can be used to help prevent the spread of COVID-19 between humans through face mask detection and a contactless thermal sensor is proposed. CNN based deep learning for the facemask detection and IR thermal sensor for non-contact human temperature measurement are used. The system is implemented locally on the Raspberry Pi platform. The training result shows the accuracy of the face mask detector is higher than 90% and stable after epoch 2. The thermal sensor shows the stable input with 0.25 deviation.

Keyphrases: cnn classifier, computer vision, contactless temperature measurement, covid 19, face mask detection

In: Tokuro Matsuo (editor). Proceedings of 11th International Congress on Advanced Applied Informatics, vol 81, pages 111-120.

Links:	https://easychair.org/publications/paper/2j2j
	https://doi.org/10.29007/fq3w

BibTeX entry

@inproceedings{IIAIAAI2021-Winter:Smart_Early_Screening_System,
  author    = {Annisa Arrahmah and Surya Ramadhan},
  title     = {Smart Early Screening System for COVID-19 Spreading Prevention},
  booktitle = {Proceedings of 11th International Congress on Advanced Applied Informatics},
  editor    = {Tokuro Matsuo},
  series    = {EPiC Series in Computing},
  volume    = {81},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/2j2j},
  doi       = {10.29007/fq3w},
  pages     = {111-120},
  year      = {2022}}

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