IoT and Machine Learning based Standalone Health Monitoring System

Tele-health is now playing a bigger part in worldwide health-care delivery. Since the epidemic hit this globe, the use of health-care surveil systems has increased dramatically. The motive of this article is to produce a prototype of a standalone health surveil system that can be placed at a case's home to replace conventional corporal checks at the sanitarium by using a BH1790GLC heart rate module and SPO2 detector to decide introductory health parameters from the case, similar as heart rate and oxygen achromatism. The heart rate and SpO2 situations are covered in real- time and displayed on the web app. This proposed system is compared to request-available movable detectors. The whole system will be powered by a PV module to make it a standalone system. The heart rate and SpO2 data is used to prognosticate if the case is suffering from complaint or can have complaint in future.