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Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras

Authors :
Ghodgaonkar, Isha
Goel, Abhinav
Bordwell, Fischer
Tung, Caleb
Aghajanzadeh, Sara
Curran, Noah
Chen, Ryan
Yu, Kaiwen
Mahapatra, Sneha
Banna, Vishnu
Kao, Gore
Lee, Kate
Hu, Xiao
Eliopolous, Nick
Chinnakotla, Akhil
Rijhwani, Damini
Kim, Ashley
Chakraborty, Aditya
Ward, Mark Daniel
Lu, Yung-Hsiang
Thiruvathukal, George K.
Publication Year :
2020

Abstract

COVID-19 has resulted in a worldwide pandemic, leading to "lockdown" policies and social distancing. The pandemic has profoundly changed the world. Traditional methods for observing these historical events are difficult because sending reporters to areas with many infected people can put the reporters' lives in danger. New technologies are needed for safely observing responses to these policies. This paper reports using thousands of network cameras deployed worldwide for the purpose of witnessing activities in response to the policies. The network cameras can continuously provide real-time visual data (image and video) without human efforts. Thus, network cameras can be utilized to observe activities without risking the lives of reporters. This paper describes a project that uses network cameras to observe responses to governments' policies during the COVID-19 pandemic (March to April in 2020). The project discovers over 30,000 network cameras deployed in 110 countries. A set of computer tools are created to collect visual data from network cameras continuously during the pandemic. This paper describes the methods to discover network cameras on the Internet, the methods to collect and manage data, and preliminary results of data analysis. This project can be the foundation for observing the possible "second wave" in fall 2020. The data may be used for post-pandemic analysis by sociologists, public health experts, and meteorologists.<br />Comment: 7 pages, 20 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2005.09091
Document Type :
Working Paper