Abstract

The sudden outbreak of the coronavirus disease (also known as COVID-19 or colloquially just as coronavirus) has disrupted our lives in numerous ways. As the virus is spreading by leaps and bounds, the healthcare systems of even the most advanced countries have reached their capacity. This is primarily because a large fraction of people infected with COVID-19 are either asymptomatic or exhibit mild symptoms. This creates a large number of reasonably healthy disease carriers, which makes it easier for the virus to reach the more vulnerable population. Because of this, contact tracing and infection tracking are indispensable for containing the spread of this pandemic. Fortunately, this coincides with the emergence of the Internet of Things (IoT), which is already being considered for healthcare applications but is a match made in heaven for contact/infection tracing because of its ubiquity. Inspired by this, we introduce a new IoT-based framework for contact and infection tracing, which specifically incorporates symptom-based detection that has been ignored in the prior art on tracing models. The ability of this framework to meaningfully merge real-time symptom information (from IoT devices) and confirmed COVID-19 cases (from medical tests) provides a fast and efficient way of tracking the disease spread, which is eventually useful for the effective utilization of the scarce resources (e.g., COVID-19 test kits). Simulation results corroborate the efficiency of our infection tracing method.

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