IoT Based Diabetes Detection through Iris Image Analysis

Abstract

Diabetes is generally caused due to high blood sugar levels. There are two types of this
polygenic disease, type one and type two. Type two is the most typical style of polygenic disease.
Polygenic disease causes severe health issues that embody cardiovascular disease, nephrosis, and eye issues.
Iridodiagnosis is a branch of science that consists of varied algorithms and is developed for image quality
assessment, Iris segmentation, Iris Normalization, Feature extraction, and classification. The developed
system uses GLCM (Gray Level Co-occurrence Matrix) to obtain texture options and for feature
classification, the SVM algorithm is employed. This approach is way quicker and efficient. Texture features
were analyzed by using ThingSpeak.