A Meta-Analysis of Artificial Intelligence Applications for Tracking COVID-19: The Case of the U.A.E.

Hala Haneya, Dhekra AlKaf, Faigah Bajammal, Tayeb Brahimi
Author Information
  1. Hala Haneya: Computer Science Department, College of Engineering, Effat University Jeddah, Saudi Arabia.
  2. Dhekra AlKaf: Computer Science Department, College of Engineering, Effat University Jeddah, Saudi Arabia.
  3. Faigah Bajammal: Computer Science Department, College of Engineering, Effat University Jeddah, Saudi Arabia.
  4. Tayeb Brahimi: Energy and Technology Research Center Natural Science, Mathematics and Technology Unit, College of Engineering, Effat University Jeddah, Saudi Arabia.

Abstract

Coronavirus disease (COVID-19) is an infectious respiratory disease that was first found in Wuhan, China, on December 31, 2019. It is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of November 10, 2020, more than fifty million cases have been confirmed, and more than one million deaths have been reported globally. This situation has created a serious challenge for all countries to institute a variety of control measures to track and slow down the spread of the virus and prevent the increasing number of deaths. In recent years, there has been an ongoing interest in using Artificial Intelligence (A.I.) in healthcare to create new treatments and detecting diseases. The objective of this study is to analyze the application and the impact of A.I. on the breakout of COVID-19 and discuss the contribution of A.I. to the fight against the pandemic based on the most recent applications used in the United Arab Emirates, including Dubai Police Movement Restriction Monitoring System, Taxis Preventive Measures Compliance System, Mobile App "Wai-Eye," Smart Helmets, Virtual Doctor, and The Department of Health - Abu Dhabi (DoH) Remote Healthcare App. The method used in this study is based on a meta-analysis of recent COVID-19 studies from various databases such as ScienceDirect, Sage Journals, SpringerLink, ResearchGate, Emerald Open Research, and IEEE Xplore. The COVID-19 data was based on Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE). Results showed that A.I. applications provided the necessary prevention of the spread of COVID-19, assisted in monitoring restrictions and preventive measures violations, and provided remote healthcare, which directly impacted the number of hospital visits amidst the lockdown. The study concluded that A.I. has proven to be effective in supporting governments in fighting the pandemic.

Keywords

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