Asymptotic Patients' Healthcare Monitoring and Identification of Health Ailments in Post COVID‐19 Scenario

Abstract

COVID-19 patients have been admitted to hospitals based on the reports of clinical symptoms associated with pulmonary disease identification. Medical Informatics has attracted attention for past five decades; however, while working with this discipline with existing artificial intelligence techniques. In EMR and CDSS, focus is then directed to the knowledge-based method, which is a very low-cost option. Over the past two decades, CBDSS (Case-Based Decision Support System), knowledge-based systems in medicine, especially in EMR (Electronic Medical Recording) and CDSS (Clinical Decision Support System), have gained a lot of interest due to the possible benefits that can be derived at a low cost. In a medical context, they can promote increasing efficiency; help diagnosis, decision-making in the management of the illness, and any other form of medical decision- making; assist in the training of medical practitioners; assist in medical study, technique, data, and information; and can also perform some routine activities in a medical environment. In this proposed methodology, we will be keeping track of heartbeat, pulse rate, geographical inclination, the temperature of the body, and the location of the patients (GPS). These parameters will be under watch for abnormalities. Reducing human intervention as much as possible, we prepared this model that will be able to keep an eye on the parameters related to the symptoms of COVID-19. As per the guidelines of WHO, the common symptoms of COVID-19 are the rise in temperature of the body and time-totime chills which are eminent and that can be observed with the help of the LM35 temperature sensor. Patients not quarantining and moving away from the prescribed place/location can be tracked using the NEO6mV2 GPS module. Around the same time, by moral judgments, it will enhance the quality of treatment and minimize the cost of care by disposing of the need for a parental figure to efficiently participate in data collection, examination, knowledge assortment, and analysis.