IOT-INSPIRED SMART HEALTHCARE FRAMEWORK FOR DIABETIC PATIENTS: FOG COMPUTING INITIATIVE

Diabetes is characterized by a high prevalence of vulnerable food habits and poor management, resulting in a high risk of premature death. Maintaining a healthy blood glucose level has several health advantages which lower the risk of diabetes. Continuous monitoring of blood glucose levels in real time is a big issue. Monitoring just glucose levels without taking account of other indicators such as ECG and physical activity, on the other hand, might lead to incorrect treatment. As a result, the ever-increasing need for an all-encompassing healthcare system has prompted the use of prominent innovations including fog-cloud computing and wireless communication network. However, complex computation, delay, and portability issues come from the use of these approaches. This paper proposes a fog computing-inspired health framework to regulate human diabetic levels to solve the aforementioned concerns. The J48Graft decision tree is utilized to forecast diabetes vulnerability with a greater level of classification accuracy. An emergency signal is issued instantly for preventive actions when fog computing is utilized. The suggested framework performs better in terms of precision, energy effectiveness, computing complexity, and delay, as evidenced by the experimental findings concerning state-of-the-art decision-making techniques.