IoT-Based COVID-19 Health Monitoring System: Context, Early Warning and Self-Adaptation

The Internet of Things (IoT) has enabled novel solutions for monitoring patients’ health through wearable sensors in conditions of both non-communicable and infectious diseases. In this paper, we report work in progress involving the development of an IoT-based COVID-19 health monitoring system that can effectively monitor the essential physiological functions of a patient through wireless sensors, thus supporting the early detection of severe cases and the continuous assessment of the patient status. The work provides several main contributions, as it includes: (i) a brief description of the current IoT-based system for remote monitoring of COVID-19 patients; (ii) a description of embedded characteristics of our device, including its contextual functions, early warning score mechanisms and self-adaptive features; and (iii) a description of our preliminary experiment results. Our proposed solution reduced drastically the amount of redundancy in data and still maintain monitoring accuracy. Given the COVID-19 scenarios, in which human resources are extended to the limit and the number of patients in severe conditions is often high, a system that can support IoT-based continuous monitoring are essential to identify changes in clinical status promptly and accurately and can potentially transform the way patients are monitored.