Research on the Relationship between Mobile Network Data and COVID-19 Cases
14th IEEE International Conference on Computer Research and Development, ICCRD 2022
; : 12-15, 2022.
Article
in English
| Scopus | ID: covidwho-1794837
ABSTRACT
During this nearly two-years-long pandemic period, the COVID-19 impacts people's lives dramatically, many people were forced to stay at home by the government's lockdown policy, and they also need to work and study at home. Therefore, there is an equivalent impact on networks as people are more dependent on them. But there are only a limited number of research has been done in this intersection area between the pandemic and networks. So, we want to fill this gap. In this paper, we will study the mobile network data from U.S. Federal Communications Commission (FCC) and COVID-19 cases data from the U.S. centers for disease control and prevention (CDC), then use machine learning to investigate the relationship between mobile network data and COVID-19 cases. We will discuss other related works, which used other methods or investigated this topic in other regions, then we will introduce our machine learning methods, experiments and give the conclusion. © 2022 IEEE.
COVID-19; Machine Learning; Mobile Networks; Mobility; Disease control; Mobile telecommunication systems; Centres for disease control and preventions; Federal Communication Commission; Intersection areas; Machine learning methods; Machine-learning; Mobile network; Network data; Related works; Wireless networks
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
14th IEEE International Conference on Computer Research and Development, ICCRD 2022
Year:
2022
Document Type:
Article
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