Your browser doesn't support javascript.
Internet of Things Framework for Oxygen Saturation Monitoring in COVID-19 Environment.
Saha, Rahul; Kumar, Gulshan; Kumar, Neeraj; Kim, Tai-Hoon; Devgun, Tannishtha; Thomas, Reji; Barnawi, Ahmed.
  • Saha R; School of Computer Science and EngineeringLovely Professional University Phagwara 144411 India.
  • Kumar G; School of Computer Science and EngineeringLovely Professional University Phagwara 144411 India.
  • Kumar N; Department of Computer Science and EngineeringThapar University Patiala 147004 India.
  • Kim TH; Department of Computer Science and Information EngineeringAsia University Taichung City 413 Taiwan.
  • Devgun T; School of Computer ScienceUniversity of Petroleum and Energy Studies Dehradun 248007 India.
  • Thomas R; Konkuk University (Glocal Campus) Seoul 27478 South Korea.
  • Barnawi A; Nokia Solutions and Networks Private Ltd. Karnal 132001 India.
IEEE Internet Things J ; 9(5): 3631-3641, 2022 Mar.
Artigo em Inglês | MEDLINE | ID: covidwho-1360420
ABSTRACT
The pandemic/epidemic of COVID-19 has affected people worldwide. A huge number of lives succumbed to death due to the sudden outbreak of this corona virus infection. The specified symptoms of COVID-19 detection are very common like normal flu; asymptomatic version of COVID-19 has become a critical issue. Therefore, as a precautionary measurement, the oxygen level needs to be monitored by every individual if no other critical condition is found. It is not the only parameter for COVID-19 detection but, as per the suggestions by different medical organizations such as the World Health Organization, it is better to use oximeter to monitor the oxygen level in probable patients as a precaution. People are using the oximeters personally; however, not having any clue or guidance regarding the measurements obtained. Therefore, in this article, we have shown a framework of oxygen level monitoring and severity calculation and probabilistic decision of being a COVID-19 patient. This framework is also able to maintain the privacy of patient information and uses probabilistic classification to measure the severity. Results are measured based on latency of blockchain creation and overall response, throughput, detection, and severity accuracy. The analysis finds the solution efficient and significant in the Internet of Things framework for the present health hazard in our world.
Palavras-chave

Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo prognóstico Idioma: Inglês Revista: IEEE Internet Things J Ano de publicação: 2022 Tipo de documento: Artigo

Similares

MEDLINE

...
LILACS

LIS


Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo prognóstico Idioma: Inglês Revista: IEEE Internet Things J Ano de publicação: 2022 Tipo de documento: Artigo