Investigating the Spread of Coronavirus Disease via Edge-AI and Air Pollution Correlation
| Autor: | R. Sitharthan, K. Janarthanan, V. Gomathy, Fadi Al-Turjman, M. Rajesh, K. Vengatesan, T. Priya Reshma |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
2019-20 coronavirus outbreak
010504 meteorology & atmospheric sciences Coronavirus disease 2019 (COVID-19) Computer Networks and Communications Computer science Mortality rate Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Air pollution 020206 networking & telecommunications 02 engineering and technology Disease medicine.disease_cause 01 natural sciences Cloud data Environmental health 0202 electrical engineering electronic engineering information engineering medicine 0105 earth and related environmental sciences Coronavirus |
| Zdroj: | ACM Transactions on Internet Technology. 21:1-10 |
| ISSN: | 1557-6051 1533-5399 |
| Popis: | Coronavirus Disease 19 (COVID-19) is a highly infectious viral disease affecting millions of people worldwide in 2020. Several studies have shown that COVID-19 results in a severe acute respiratory syndrome and may lead to death. In past research, a greater number of respiratory diseases has been caused by exposure to air pollution for long periods of time. This article investigates the spread of COVID-19 as a result of air pollution by applying linear regression in machine learning method based edge computing. The analysis in this investigation have been based on the death rates caused by COVID-19 as well as the region of death rates based on hazardous air pollution using data retrieved from the Copernicus Sentinel-5P satellite. The results obtained in the investigation prove that the mortality rate due to the spread of COVID-19 is 77% higher in areas with polluted air. This investigation also proves that COVID-19 severely affected 68% of the individuals who had been exposed to polluted air. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|