Investigation of Blockchain for COVID-19: A Systematic Review, Applications and Possible Challenges

Smart city is emerging application in which many Internet of Things (IoT) devices are embedded to perform overall monitoring and perform processing automatically. In smart city the authenticity is key problem and many users in the in smart city has faced challenges during COVID-19. The COVID-19 epid...

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Veröffentlicht in:EAI endorsed transactions on smart cities 2023-03, Vol.7 (1), p.e4
Hauptverfasser: Shah Hussain Badshah, Muhammad Imad, Muhammad Abul Hassan, Naimullah, Shabir khan, Farhatullah, Sana Ullah, Syed Haider Ali
Format: Artikel
Sprache:eng
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Zusammenfassung:Smart city is emerging application in which many Internet of Things (IoT) devices are embedded to perform overall monitoring and perform processing automatically. In smart city the authenticity is key problem and many users in the in smart city has faced challenges during COVID-19. The COVID-19 epidemic, a deadly virus, first appeared in the globe in 2019. The World Health Organization (WHO) states that it is almost certainly feasible to contain this virus in its early phases if some precautions are taken. To contain the infection, most nations declared emergencies both inside and outside their borders and prohibited travel. Artificial intelligence and blockchain are being used in smart city applications to monitor the general condition in the nation and reduce the mortality rate. Blockchain has also made it possible to safeguard patient medical histories and provide epidemic tracking. AI also offers the ideal, wanted answer for correctly identifying the signs. The primary goal of this study is to fully investigate blockchain technology and artificial intelligence (AI) in relation to COVID-19. A case study that was recently developed to identify and networked pathogens acquired important knowledge and data. Additionally, AI that can handle massive quantities of medical data and perform difficult jobs will be able to reduce the likelihood of intricacy in data analysis. Lastly, we highlight the present difficulties and suggest potential paths for addressing the 19 diseases in future circumstances.
ISSN:2518-3893
2518-3893
DOI:10.4108/eetsc.v7i1.2827