ABSTRACT
The pandemic of COVID-19 disease started from Wuhan city of China and spread across the globe within a few months. This highly contagious disease has spread the infection to millions of people in a short duration of time. Such an exponentially increased number of patients has presented several challenges for health infrastructures. One of the major challenges is to cope with a large number of patients with limited resources. The medical practitioners find it difficult to effectively distribute their time for the patients based on the severity of the health condition. This chapter presents an Internet of Things (IoT) based framework in which a patient’s health condition is automatically categorized into different levels of severity by means of objectively measured health markers. Some of the health markers such as SpO2 level and body temperature are suggested for the objective means of monitoring in the selected framework. In this chapter, recursive feature elimination method is used to identify important symptoms (health marker) in order to reduce the mortality rate. These features are incorporated in the three-layered architecture of IoT for final categorization of health condition. The classification algorithm in the third layer categorizes the patients’ health condition into different categories of severity. It communicates between the mobile devices from patients and doctor which facilitate the doctor about meta-level health conditions for particular category of patients. The results obtained by considering 472 patients’ data show the potential of the proposed framework in reducing doctor’s workload by reducing the time for assessment of severity about health condition.
