Smart Contact Tracing and Classifier System for Covid-19 Cases

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.