Common Disease Proneness Prediction Using IOT and Artificial Intelligence

Computer Engineering

Monitoring of various health parameters every day is not viable as it requires the investment of a lot of time and effort. Travelling all the way to the clinic for a doctor’s appointment daily is quite expensive and time-consuming. As the Vital signs and other parameters can be monitored by various gadgets, such as wearable sensors and fitness trackers as well as smartphones nowadays. Most of their gadgets are small and portable in nature as they are supposed to be worn or carried without any inconvenience, which in turn reduces the battery capacity as well as the memory of the device to fit in such a form factor, which limits the scope of Healthcare predictions. Therefore, to ameliorate this effect, the researchers have implemented a technique that utilizes the IoT platform to outsource the recorded data on to the server. The server employs K Nearest Neighbour and Artificial Neural Network that is capable of accurately predicting the Health conditions of a person with the help of parameters, such as Pulse Rate, Blood sugar level, body temperature, etc.

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