Artificial Electronic Nurse : An IoT Based Health Monitoring System

Abstract: Context. Generally, health monitoring systems are used in hospitals, which are pricey and gigantic. But with the up gradation of sensors and modules, these devices are also available in portable sizes. These devices are divided into different types according to the disease. So, our project aims to provide a device with multiple parameters monitoring with fall detection, and it is budget-friendly.  Objectives. The objective of our project is to provide freedom to users and monitor simultaneously, using IoT and sensors. People with an illness that may be physical or mental, children, and older people with some issues. They are the users of our idea. Generally, they need to be monitored by a person, which is costly and requires endurance. So, the main objective is to monitor the patient’s health condition and alert in an emergency and store the data on the user’s health.  Methods. After a lot of observation, we found that we can monitor the patient’s health status using an ESP32 Wroom dev kit, which is a microcontroller that consists of Bluetooth and Wi-Fi. We use an MPU6050 accelerometer that detects the falling and motion of the user using three axial movements. We use MAX30102 pulse oximetry which measures the oxygen level, pulse rate, and temperature. Along with these, we use a mobile application that receives data and stores it.  Results. The device reads the parameters regularly and stores the data in the cloud or mobile application. It contains a push button that alerts the relatives and respected authorities. It transmits the location. Finally, it will trigger the command of alerting when the user falls. Conclusions. Every person can use our health monitoring system. The person should wear the device properly and be connected to the Wi-Fi. Once the fall is detected, the contacts are notified. And the detection is more accurate. Regular usage of the device increases the accuracy and analysis of the user’s health.