Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/11682
Title: CoviIS: A Real-Time Covid Help Information System Using Digital Media
Authors: Ganji, Niharika
Bansal, Shubhi
Kumar, Nagendra
Keywords: Information systems;Information use;Search engines;Social networking (online);Covid assistance;Geographical analysis;Informatics;Multiple methods;News articles;News search;Real- time;Social media;Social media searches;Time of crisis;Digital storage
Issue Date: 2023
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Ganji, N., Sinhamahapatra, A., Bansal, S., & Kumar, N. (2023). CoviIS: A real-time covid help information system using digital media doi:10.1007/978-981-19-6634-7_50 Retrieved from www.scopus.com
Abstract: In this paper, we present CoviIS, an emergency Covid Information System that utilizes digital media to provide helpful information in uncertain times of the Covid pandemic. Since people require different types of information during times of crisis, the findings obtained from this work integrate various pieces of information into a form of coherency, thereby aiding people during an emergency and reducing further damage. The study brings together real-time Covid informatics employing multiple methods such as general search, social media search, and geographical analysis. To assist people in this emergency, we also conduct a comprehensive analysis of news articles and social media activities to provide an economically feasible solution. CoviIS helps locate the nearest hospitals and Covid isolation centers for seeking medical attention during an emergency. CoviIS also provides emergency information through news articles and social media posts, thereby serving as an important Covid emergency tool. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
URI: https://doi.org/10.1007/978-981-19-6634-7_50
https://dspace.iiti.ac.in/handle/123456789/11682
ISSN: 2367-3370
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

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