Fuzzy Logic-Based Smart Healthcare System for Preliminary Identification of Patients with Pandemic-Prone Diseases Through Symptom Analysis

A pandemic is a disease outbreak that alarmingly affects a high percentage of people across the globe. Covid-19 is the most recent lethal disease that has caused global devastation. In addition to having a significant negative influence on people's socio-economic lives, it has marked a crucial impact on sustainable healthcare and the environment. Early detection of Covid-19 is essential for the effective management of the disease to halt its rapid spread. It enables the implementation of smart technologies for remote healthcare to safeguard public health. In light of this, the current work presents fuzzy logic-based smart, and sustainable healthcare system for the preliminary identification of Covid-19 patients based on their symptoms. After getting validated on several test subjects under the supervision of medical professionals, this support system appears to be an effective solution for the preliminary detection of Covid-19 in the home or clinical scenarios.