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

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras
Creator	Kim, Ashley Hu, Xiao Ward, Mark Aghajanzadeh, Sara Banna, Vishnu Bordwell, Fischer Chakraborty, Aditya Chen, Ryan Chinnakotla, Akhil Curran, Noah Eliopolous, Nick Ghodgaonkar, Isha Goel, Abhinav Kao, Gore Lee, Kate Lu, Yung-Hsiang Mahapatra, Sneha Rijhwani, Damini Thiruvathukal, George Tung, Caleb Yu, Kaiwen
source	ArXiv
abstract	COVID-19 has resulted in a worldwide pandemic, leading to%22lockdown%22policies 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%22second wave%22in fall 2020. The data may be used for post-pandemic analysis by sociologists, public health experts, and meteorologists.
has issue date	2020-05-18(xsd:dateTime)
has license	arxiv
sha1sum (hex)	9e22cb848eed15151749d1449998cba1d8385046
resource representing a document's title	Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras
resource representing a document's body	covid:9e22cb848eed15151749d1449998cba1d8385046#body_text
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