ABSTRACT
Keeping vigil on health parameters on a daily basis is a cumbersome task and it needs a lot of effort and time. Even visiting the doctor on a daily basis also needs financial backup. Monitoring of the health parameters is carried out by many systems and gadgets like smartwatches, wearable devices, and sensors. Due to limited primary memory, they are rarely used and have no scope of prediction of health conditions. So, to think beyond this point, this chapter uses the Internet of Things through which the data is collected about the patients from sensors at the server end. The server is equipped with the finest machine learning algorithm like K-means clustering and artificial neural networks to predict the future health conditions of the patients or users. The proposed model uses some parameters like systolic blood pressure, diastolic blood pressure, body temperature, blood sugar level, and pulse rate.
