Title: Artificial intelligence-based algorithm to track the probable COVID-19 cases using contact history of virus infected person

Authors: Javed Shaikh; R.S. Singh; Demissie Jobir Gelmecha; Tadesse Hailu Ayane

Addresses: Electronics and Communication Engineering Department, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, Oromia, Ethiopia ' Electronics and Communication Engineering Department, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, Oromia, Ethiopia ' Electronics and Communication Engineering Department, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, Oromia, Ethiopia ' Electronics and Communication Engineering Department, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, Oromia, Ethiopia

Abstract: Currently, the world is facing major challenges in tackling COVID-19. It has affected many countries of the world in terms of human lives, economy and so many other aspects. Many organisations and scientists are working to find the way in which the spread of the COVID-19 can be minimised. One technology which can be effective in tackling this virus is Artificial Intelligence (AI). There are many ways in which AI can help in tackling with this virus. The foremost requirement of this situation is to find the cases of infections as early as possible so that it will not spread rapidly. In this paper, an artificial intelligence-based algorithm is proposed for the tracking of probable COVID-19 cases. The algorithm uses the mobile numbers of corona virus infected person as data for the forecasting. This technique will find the probable infected cases and help in controlling rapid spread of virus. This method will provide information regarding an infected person who had contacted to other persons by using forecasting method. As this is automated tracking system it will help in finding the probable virus infected cases with very short time.

Keywords: COVID-19; artificial intelligence; machine learning; forecasting methods.

DOI: 10.1504/IJCAT.2021.119768

International Journal of Computer Applications in Technology, 2021 Vol.66 No.2, pp.145 - 153

Received: 14 Jun 2020
Accepted: 18 Oct 2020
Published online: 20 Dec 2021 *

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