In this project, we use IoT devices to measure health data such as heart rate, blood oxygen, number of steps per day of a person and then send them through Bluetooth to Raspberry Pi. The data will then be saved in MongoDB Atlas and updated daily.
Besides, the data will also be analysed using a Machine Learning model called K-Means Neighbours to predict if a person is likely to have heart disease in the next 10 years.
The data which is used to train the model is the combination of the data measured by the IoT devices and from the Kaggle dataset. So the correctness of the data is relatively high.
Due to the shortage of data and the simplicity of the model, the accuracy of its is around 80%, which is not very high due to lots of model at this time.