Traditionally, public health researchers gathered health data through direct observation and testing, or Electronic Medical Records (EMR). The collected data was often in paper form and stored at the researcher’s own facility. Research objectives and data processing were only discussed with Institutional Review Boards (IRBs) with no negotiation between researchers and data subjects beyond collecting informed consent.

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.