Open AccessSmart Contact Tracing and Classifier System for Covid-19 Cases
Author(s) -
Moko Anasuodei,
Amannah Izuchukwu
Publication year - 2021
Publication title -
international journal of emerging trends in engineering research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 14
ISSN - 2347-3983
DOI - 10.30534/ijeter/2021/06992021
Subject(s) - contact tracing , tracing , covid-19 , classifier (uml) , bluetooth , computer science , artificial intelligence , machine learning , wireless , operating system , infectious disease (medical specialty) , medicine , disease , pathology
The growing shreds of evidence and spread of COVID-19 in recent times have shown that to effortlessly and optimally tackle the rate at which COVID-19 infected individuals affect uninfected individuals has become a pressing challenge. This demands the need for a smart contact tracing method for COVID-19 contact tracing. This paper reviewed and analysed the available contact tracing models, contact tracing applications used by 36 countries, and their underlined classifier systems and techniques being used for COVID-19 contact tracing, machine learning classifier methods and ways in which these classifiers are evaluated. The incremental method was adopted because it results in a step-by-step rule set that continually changes. Three categories of learning classifier systems were also studied and recommended the Smartphone Mobile Bluetooth (BLE) and Michigan learning classifier system because it offers a short-range communication that is available regardless of the operating system and classifies based on set rules quickly and faster.