Health Disease Prediction Using Deep Learning And Patient Health Monitoring Wearable Device Using Sensors And IOT

Abstract

In spite of several emerging medical technologies and innovations, many countries are facing difficulties in creating the proper health infrastructure which can handle pandemic and emergency situations. So, it is essential to have a smart and virtual health infrastructure to track, test and treat the patients. The proposed model adopts IOT based wearable device which includes multiple sensors to observe the health condition of the patient. The sensors data obtained from the wearable device will be periodically uploaded to cloud user account. Additional access will be given to doctor/care takers to load the test results and medications. So we have used HTTP protocol over internet or LAN (local area network). We have implemented wearable device where it reads pulse rate and temperature every 8 sec and upload the data in Things speak which is an IOT platform where doctor’s, patient care taker and nurse can monitor patients health by sitting any corner of this world and Now-a-days, People nowadays suffer from a variety of diseases as a result of the climate and their lifestyle choices. As a result, predicting illness at an earlier stage becomes a critical challenge. However, doctors find it difficult to make precise predictions based on symptoms. The most difficult challenge is correctly predicting disease. To solve this issue, a computer was developed. Training is crucial in predicting the future. We proposed general disease prediction based on symptoms of the patient.