IoT System in Diagnosis of Covid-19 Patients

Dan Cacovean (), Irina Ioana () and Gabriela Nitulescu ()

Informatica Economica, 2020, vol. 24, issue 2, 75-89

Abstract: Implementation of an IoT system for the detection of Covid-infected 19. A sample of 300 people participated in this experiment. They are assigned wearables that they must wear for a period of one week throughout the day. The data is retrieved in real time at an interval of 60 minutes. These wearables are equipped with temperature, heart rate and GPS sensors to determine people inside or outside virus outbreaks. The data is then retrieved and sent to Oracle Cloud. Here they are processed according to Machine Learning algorithms and sent predictions to the subjects' family doctors, but also to the national health system. If patients are suspected of being infected with the virus, then they should be contacted as soon as possible for testing.

Keywords: Internet of Things; healthcare; health-Iot; software; hardware; cloud (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://revistaie.ase.ro/content/94/07%20-%20cacovean,%20ioana,%20nitulescu.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aes:infoec:v:24:y:2020:i:2:p:75-89

Access Statistics for this article

Informatica Economica is currently edited by Ion Ivan

More articles in Informatica Economica from Academy of Economic Studies - Bucharest, Romania Contact information at EDIRC.
Bibliographic data for series maintained by Paul Pocatilu ().