Predicting Illnesses from Medical Sensors Readings using Artificial Intelligence Model

The cost and lack of flexibility of health care systems represent a major obstacle for the elderly and poor citizens. The current technologies are reserved for hospitals and large clinics in the developed countries have high costs and maintenance. Therefore, it is necessary to bring health monitoring closer to the patients and healthcare providers in a cost-effective way. This study aims to build a platform that is ready to expand to use all the sensors to predict illnesses and conditions in hospitals and homes. The system is based on two Arduino Uno microcontroller units (MCU), environmental sensors, health sensors (MySignals), and Arduino IDE. Fuzzy Logic is used to push and pull data from the cloud to mobile and web visualization plus an alert system. This study tested 15 sensors in both health and ambient environments the integration of both groups of sensors can produce more accurate predictions. In addition, metrics will be used to decide the range of readings that are industry-specific for each sensor.