Open Access

ARTICLE

Systematic Survey on Big Data Analytics and Artificial Intelligence for COVID-19 Containment

Saeed M. Alshahrani¹, Jameel Almalki², Waleed Alshehri², Rashid Mehmood³, Marwan Albahar², Najlaa Jannah², Nayyar Ahmed Khan^1,*

1 Department of Computer Science, College Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia
2 Department of Computer Science, College of Computer in Al-Lith, Umm Al-Qura University, Makkah, Saudi Arabia
3 High-Performance Computing Center, King Abdulaziz University, Jeddah, Saudi Arabia

* Corresponding Author: Nayyar Ahmed Khan. Email:

Computer Systems Science and Engineering 2023, 47(2), 1793-1817. https://doi.org/10.32604/csse.2023.039648

Received 09 February 2023; Accepted 09 May 2023; Issue published 28 July 2023

Abstract

Artificial Intelligence (AI) has gained popularity for the containment of COVID-19 pandemic applications. Several AI techniques provide efficient mechanisms for handling pandemic situations. AI methods, protocols, data sets, and various validation mechanisms empower the users towards proper decision-making and procedures to handle the situation. Despite so many tools, there still exist conditions in which AI must go a long way. To increase the adaptability and potential of these techniques, a combination of AI and Bigdata is currently gaining popularity. This paper surveys and analyzes the methods within the various computational paradigms used by different researchers and national governments, such as China and South Korea, to fight against this pandemic. The process of vaccine development requires multiple medical experiments. This process requires analyzing datasets from different parts of the world. Deep learning and the Internet of Things (IoT) revolutionized the field of disease diagnosis and disease prediction. The accurate observations from different datasets across the world empowered the process of drug development and drug repurposing. To overcome the issues generated by the pandemic, using such sophisticated computing paradigms such as AI, Machine Learning (ML), deep learning, Robotics and Bigdata is essential.

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