Risk analysis of diabetes using IoT and deep learning

Abstract

Diabetes mellitus is a most common disease faced by most of patients can have uncontrollable glucose level can lead to chronic disease to prevent this risk of higher chances of chronic diseases which can be implemented using Internet of Things(IoT) which is applied in various areas for solving problems of healthcare involved in monitoring and diagnosis of different parts of body using wearables or biosensors. In the proposed system, IoT devices and cloud technologies are connected to transfer data and execute the decisions on well-defined rules and deep learning technique is applied on diabetes data to decide the risk of diabetic patient which is solved by defining rules, system can understand the which data lies under which partition and knowledge representation can be made using the result the system can decide whether to suggest lifestyle modifications or proper in-take medication for improving their health and reduce adverse reactions in other parts of body or preventing to cause psychological effects.