Light sensor optimization based on finger blood estimation and IoT-integrated

Abstract

Diabetes mellitus is a prevalent disease in society. This condition results from various causes, such as lifestyle choices or genetic predisposition. To prevent diabetes mellitus, blood glucose levels must be monitored periodically, and dietary consumption must be managed. Blood glucose monitoring still uses the incision or minimally invasive approach. This approach poses a risk of infection and damage. This study devised a method to optimize a light sensor to measure blood glucose levels. This approach uses sensor optimization and an integrated Internet of Things (IoT) technology. The research findings demonstrate that the use of the optimization strategy leads to increased consistency in sensor values, which may then be transmitted wirelessly through the IoT network. The research results demonstrate that using the optimization strategy leads to increased consistency in sensor values, which may then be wirelessly transmitted through the IoT network.