Real-Time Analysis of Wearable Sensor Data Using IoT and Machine Learning in Healthcare
Keywords:
Patient monitoring system, controller, pulse rate sensor, temperature sensor, AR glasses, IoTAbstract
Practitioners in the medical field are always on the hunt for new tools that can improve their workflow. There have been several developments in the operating room as a result of the digital age's impact on the clinical environment. The purpose of this study is to reduce the likelihood of burnout while providing better treatment to patients. The LM35 and pulse sensor in the system measure the user's core body temperature, heart rate, and breathing rate. The Arduino UNO controller board communicates with each of these sensors. The WiFi module's data transmissions are tracked by use of AR glasses. Adafruit, an Internet of Things platform, stores sensor data reserved by the ESP8266 WiFi module. In this way, the medical history of the patients may be accessed whenever necessary. When the data from the sensors is too high, an alarm is sent to the surgeon. As a result, the prototype facilitates the doctor's ongoing monitoring of patient data.The use of IoT(Internet of Things) with Machine Learning can help use to solve this issue
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