An Automatic Diabetes Risk Assessment System Using IoT Cloud Platform

Abstract

Diabetes mellitus is a disease that impairs the body’s ability to process blood sugar due to insufficient production of the hormone called insulin or the body’s resistant towards insulin or both. There are three types of diabetes, namely, type 1, type 2, and gestational diabetes. Among these types, type 2 is common and it is associated with lifestyle risk factors such as inadequate physical activity, poor diet and increased body mass index and hereditary factors. If it is not managed carefully, diabetes can lead to a accumulation of blood sugars which can increase the risk of obtaining stroke, heart and kidney diseases. Therefore a personalized advisory system which monitors the health condition of the user through sensors acquire his/her diet and day-to-day activity information through interactive platforms, store them in a common cloud platform, process them through machine learning techniques, and provide valid health related personalized advices to manage their health condition is the need of the hour (American Diabetes Association, Diabetes Care 29:s4–s42, 2006). The proposed system uses an IoT Cloud platform named ThingSpeak, where the sensor data can be sent to the cloud for storing, analyzing, and visualizing the data with MATLAB or other software and our own applications can be developed and operated by MathWorks. A web application has been developed and made available to the users to manage diabetes or prevent them from diabetes and its dangerous complications.