A Covid-19 viral transmission prevention system for embedded devices utilising deep learning

Mihai Penica; Reenu Mohandas; Mangolika Bhattacharya; Karl Vancamp; Martin Hayes; Eoin O'Connell

doi:10.1109/ISSC52156.2021.9467847

A Covid-19 viral transmission prevention system for embedded devices utilising deep learning

Mihai Penica
, Reenu Mohandas
, Mangolika Bhattacharya
, Karl Vancamp
, Martin Hayes
, Eoin O'Connell

University of Limerick

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The coronavirus pandemic (COVID-19) has created an urgent need for different monitoring systems to prevent viral transmission because of its severity and contagious aspect. This paper proposes design and implementation of a hardware-software solution that uses supervised machine learning algorithms to examine an individual and determine if he/she poses a viral transmission danger. The solution proposed was developed utilising an ARM embedded device along with different sensors to detect and monitor COVID-19 symptoms and, at the same time, to enforce wearing of a mask by using deep learning computer vision.

Original language	English
Title of host publication	2021 32nd Irish Signals and Systems Conference, ISSC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665434294
DOIs	https://doi.org/10.1109/ISSC52156.2021.9467847
Publication status	Published - 10 Jun 2021
Event	32nd Irish Signals and Systems Conference, ISSC 2021 - Athlone, Ireland Duration: 10 Jun 2021 → 11 Jun 2021

Publication series

Name	2021 32nd Irish Signals and Systems Conference, ISSC 2021

Conference

Conference	32nd Irish Signals and Systems Conference, ISSC 2021
Country/Territory	Ireland
City	Athlone
Period	10/06/21 → 11/06/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

COVID-19 symptoms
artificial intelligence
covid19 viral transmission
health monitoring
raspberry pi

Access to Document

10.1109/ISSC52156.2021.9467847

Cite this

Penica, M., Mohandas, R., Bhattacharya, M., Vancamp, K., Hayes, M., & O'Connell, E. (2021). A Covid-19 viral transmission prevention system for embedded devices utilising deep learning. In 2021 32nd Irish Signals and Systems Conference, ISSC 2021 Article 9467847 (2021 32nd Irish Signals and Systems Conference, ISSC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSC52156.2021.9467847

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title = "A Covid-19 viral transmission prevention system for embedded devices utilising deep learning",

abstract = "The coronavirus pandemic (COVID-19) has created an urgent need for different monitoring systems to prevent viral transmission because of its severity and contagious aspect. This paper proposes design and implementation of a hardware-software solution that uses supervised machine learning algorithms to examine an individual and determine if he/she poses a viral transmission danger. The solution proposed was developed utilising an ARM embedded device along with different sensors to detect and monitor COVID-19 symptoms and, at the same time, to enforce wearing of a mask by using deep learning computer vision.",

keywords = "COVID-19 symptoms, artificial intelligence, covid19 viral transmission, health monitoring, raspberry pi",

author = "Mihai Penica and Reenu Mohandas and Mangolika Bhattacharya and Karl Vancamp and Martin Hayes and Eoin O'Connell",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 32nd Irish Signals and Systems Conference, ISSC 2021 ; Conference date: 10-06-2021 Through 11-06-2021",

year = "2021",

month = jun,

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doi = "10.1109/ISSC52156.2021.9467847",

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Penica, M, Mohandas, R, Bhattacharya, M, Vancamp, K, Hayes, M & O'Connell, E 2021, A Covid-19 viral transmission prevention system for embedded devices utilising deep learning. in 2021 32nd Irish Signals and Systems Conference, ISSC 2021., 9467847, 2021 32nd Irish Signals and Systems Conference, ISSC 2021, Institute of Electrical and Electronics Engineers Inc., 32nd Irish Signals and Systems Conference, ISSC 2021, Athlone, Ireland, 10/06/21. https://doi.org/10.1109/ISSC52156.2021.9467847

A Covid-19 viral transmission prevention system for embedded devices utilising deep learning. / Penica, Mihai; Mohandas, Reenu; Bhattacharya, Mangolika et al.
2021 32nd Irish Signals and Systems Conference, ISSC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 9467847 (2021 32nd Irish Signals and Systems Conference, ISSC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hayes, Martin

AU - O'Connell, Eoin

PY - 2021/6/10

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N2 - The coronavirus pandemic (COVID-19) has created an urgent need for different monitoring systems to prevent viral transmission because of its severity and contagious aspect. This paper proposes design and implementation of a hardware-software solution that uses supervised machine learning algorithms to examine an individual and determine if he/she poses a viral transmission danger. The solution proposed was developed utilising an ARM embedded device along with different sensors to detect and monitor COVID-19 symptoms and, at the same time, to enforce wearing of a mask by using deep learning computer vision.

AB - The coronavirus pandemic (COVID-19) has created an urgent need for different monitoring systems to prevent viral transmission because of its severity and contagious aspect. This paper proposes design and implementation of a hardware-software solution that uses supervised machine learning algorithms to examine an individual and determine if he/she poses a viral transmission danger. The solution proposed was developed utilising an ARM embedded device along with different sensors to detect and monitor COVID-19 symptoms and, at the same time, to enforce wearing of a mask by using deep learning computer vision.

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KW - artificial intelligence

KW - covid19 viral transmission

KW - health monitoring

KW - raspberry pi

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DO - 10.1109/ISSC52156.2021.9467847

M3 - Conference contribution

AN - SCOPUS:85114445913

T3 - 2021 32nd Irish Signals and Systems Conference, ISSC 2021

BT - 2021 32nd Irish Signals and Systems Conference, ISSC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 32nd Irish Signals and Systems Conference, ISSC 2021

Y2 - 10 June 2021 through 11 June 2021

ER -

Penica M, Mohandas R, Bhattacharya M, Vancamp K, Hayes M , O'Connell E. A Covid-19 viral transmission prevention system for embedded devices utilising deep learning. In 2021 32nd Irish Signals and Systems Conference, ISSC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. 9467847. (2021 32nd Irish Signals and Systems Conference, ISSC 2021). doi: 10.1109/ISSC52156.2021.9467847

A Covid-19 viral transmission prevention system for embedded devices utilising deep learning

Abstract

Publication series

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UN SDGs

Keywords

Access to Document

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Cite this