Tracking COVID-19 by Tracking Infectious Trajectories
Nowadays, the coronavirus pandemic has and is still causing large numbers of deaths and infected people. Although governments all over the world have taken severe measurements to slow down the virus spreading (e.g., travel restrictions, suspending all sportive, social, and economic activities, quara...
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doaj-cb93cb515bc847ac845481e77d5d48bc2021-03-30T04:05:00ZengIEEEIEEE Access2169-35362020-01-01814524214525510.1109/ACCESS.2020.30150029162031Tracking COVID-19 by Tracking Infectious TrajectoriesBadreddine Benreguia0https://orcid.org/0000-0002-1181-3950Hamouma Moumen1https://orcid.org/0000-0002-1986-7590Mohammed Amine Merzoug2https://orcid.org/0000-0002-5316-6456Computer Science Department, University of Batna 2, Batna, AlgeriaComputer Science Department, University of Batna 2, Batna, AlgeriaComputer Science Department, University of Batna 2, Batna, AlgeriaNowadays, the coronavirus pandemic has and is still causing large numbers of deaths and infected people. Although governments all over the world have taken severe measurements to slow down the virus spreading (e.g., travel restrictions, suspending all sportive, social, and economic activities, quarantines, social distancing, etc.), a lot of persons have died and a lot more are still in danger. Indeed, a recently conducted study [1] has reported that 79% of the confirmed infections in China were caused by undocumented patients who had no symptoms. In the same context, in numerous other countries, since coronavirus takes several days before the emergence of symptoms, it has also been reported that the known number of infections is not representative of the real number of infected people (the actual number is expected to be much higher). That is to say, asymptomatic patients are the main factor behind the large quick spreading of coronavirus and are also the major reason that caused governments to lose control over this critical situation. To contribute to remedying this global pandemic, in this article, we propose an IoT<sup>a</sup> investigation system that was specifically designed to spot both undocumented patients and infectious places. The goal is to help the authorities to disinfect high-contamination sites and confine persons even if they have no apparent symptoms. The proposed system also allows determining all persons who had close contact with infected or suspected patients. Consequently, rapid isolation of suspicious cases and more efficient control over any pandemic propagation can be achieved.https://ieeexplore.ieee.org/document/9162031/Big datacoronavirusCOVID-19infection trackinginformation and communications technologiesInternet of Things |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Badreddine Benreguia Hamouma Moumen Mohammed Amine Merzoug |
spellingShingle |
Badreddine Benreguia Hamouma Moumen Mohammed Amine Merzoug Tracking COVID-19 by Tracking Infectious Trajectories IEEE Access Big data coronavirus COVID-19 infection tracking information and communications technologies Internet of Things |
author_facet |
Badreddine Benreguia Hamouma Moumen Mohammed Amine Merzoug |
author_sort |
Badreddine Benreguia |
title |
Tracking COVID-19 by Tracking Infectious Trajectories |
title_short |
Tracking COVID-19 by Tracking Infectious Trajectories |
title_full |
Tracking COVID-19 by Tracking Infectious Trajectories |
title_fullStr |
Tracking COVID-19 by Tracking Infectious Trajectories |
title_full_unstemmed |
Tracking COVID-19 by Tracking Infectious Trajectories |
title_sort |
tracking covid-19 by tracking infectious trajectories |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Nowadays, the coronavirus pandemic has and is still causing large numbers of deaths and infected people. Although governments all over the world have taken severe measurements to slow down the virus spreading (e.g., travel restrictions, suspending all sportive, social, and economic activities, quarantines, social distancing, etc.), a lot of persons have died and a lot more are still in danger. Indeed, a recently conducted study [1] has reported that 79% of the confirmed infections in China were caused by undocumented patients who had no symptoms. In the same context, in numerous other countries, since coronavirus takes several days before the emergence of symptoms, it has also been reported that the known number of infections is not representative of the real number of infected people (the actual number is expected to be much higher). That is to say, asymptomatic patients are the main factor behind the large quick spreading of coronavirus and are also the major reason that caused governments to lose control over this critical situation. To contribute to remedying this global pandemic, in this article, we propose an IoT<sup>a</sup> investigation system that was specifically designed to spot both undocumented patients and infectious places. The goal is to help the authorities to disinfect high-contamination sites and confine persons even if they have no apparent symptoms. The proposed system also allows determining all persons who had close contact with infected or suspected patients. Consequently, rapid isolation of suspicious cases and more efficient control over any pandemic propagation can be achieved. |
topic |
Big data coronavirus COVID-19 infection tracking information and communications technologies Internet of Things |
url |
https://ieeexplore.ieee.org/document/9162031/ |
work_keys_str_mv |
AT badreddinebenreguia trackingcovid19bytrackinginfectioustrajectories AT hamoumamoumen trackingcovid19bytrackinginfectioustrajectories AT mohammedaminemerzoug trackingcovid19bytrackinginfectioustrajectories |
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