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A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media

Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was firstly reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. Coronavir...

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Autores principales: Butt, Muhammad Junaid, Malik, Ahmad Kamran, Qamar, Nafees, Yar, Samad, Malik, Arif Jamal, Rauf, Usman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303179/
https://www.ncbi.nlm.nih.gov/pubmed/37420714
http://dx.doi.org/10.3390/s23125543
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author Butt, Muhammad Junaid
Malik, Ahmad Kamran
Qamar, Nafees
Yar, Samad
Malik, Arif Jamal
Rauf, Usman
author_facet Butt, Muhammad Junaid
Malik, Ahmad Kamran
Qamar, Nafees
Yar, Samad
Malik, Arif Jamal
Rauf, Usman
author_sort Butt, Muhammad Junaid
collection PubMed
description Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was firstly reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. Coronavirus has been the cause of millions of deaths around the world. Furthermore, many countries are struggling with COVID-19 and have experimented with various kinds of vaccines to eliminate the deadly virus and its variants. This survey deals with COVID-19 data analysis and its impact on human social life. Data analysis and information related to coronavirus can greatly help scientists and governments in controlling the spread and symptoms of the deadly coronavirus. In this survey, we cover many areas of discussion related to COVID-19 data analysis, such as how artificial intelligence, along with machine learning, deep learning, and IoT, have worked together to fight against COVID-19. We also discuss artificial intelligence and IoT techniques used to forecast, detect, and diagnose patients of the novel coronavirus. Moreover, this survey also describes how fake news, doctored results, and conspiracy theories were spread over social media sites, such as Twitter, by applying various social network analysis and sentimental analysis techniques. A comprehensive comparative analysis of existing techniques has also been conducted. In the end, the Discussion section presents different data analysis techniques, provides future directions for research, and suggests general guidelines for handling coronavirus, as well as changing work and life conditions.
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spelling pubmed-103031792023-06-29 A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media Butt, Muhammad Junaid Malik, Ahmad Kamran Qamar, Nafees Yar, Samad Malik, Arif Jamal Rauf, Usman Sensors (Basel) Review Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was firstly reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. Coronavirus has been the cause of millions of deaths around the world. Furthermore, many countries are struggling with COVID-19 and have experimented with various kinds of vaccines to eliminate the deadly virus and its variants. This survey deals with COVID-19 data analysis and its impact on human social life. Data analysis and information related to coronavirus can greatly help scientists and governments in controlling the spread and symptoms of the deadly coronavirus. In this survey, we cover many areas of discussion related to COVID-19 data analysis, such as how artificial intelligence, along with machine learning, deep learning, and IoT, have worked together to fight against COVID-19. We also discuss artificial intelligence and IoT techniques used to forecast, detect, and diagnose patients of the novel coronavirus. Moreover, this survey also describes how fake news, doctored results, and conspiracy theories were spread over social media sites, such as Twitter, by applying various social network analysis and sentimental analysis techniques. A comprehensive comparative analysis of existing techniques has also been conducted. In the end, the Discussion section presents different data analysis techniques, provides future directions for research, and suggests general guidelines for handling coronavirus, as well as changing work and life conditions. MDPI 2023-06-13 /pmc/articles/PMC10303179/ /pubmed/37420714 http://dx.doi.org/10.3390/s23125543 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Butt, Muhammad Junaid
Malik, Ahmad Kamran
Qamar, Nafees
Yar, Samad
Malik, Arif Jamal
Rauf, Usman
A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media
title A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media
title_full A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media
title_fullStr A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media
title_full_unstemmed A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media
title_short A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media
title_sort survey on covid-19 data analysis using ai, iot, and social media
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303179/
https://www.ncbi.nlm.nih.gov/pubmed/37420714
http://dx.doi.org/10.3390/s23125543
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