AI-based Diabetic Retinopathy Grading Using Raspberry Pi

Diabetic retinopathy is a progressive eye condition caused by prolonged high blood sugar levels in individuals with diabetes, leading to damage in the blood vessels of the retina. It can result in vision impairment or blindness if left untreated, making early detection and management crucial for preserving eyesight. Employing neural networks for image classification can help overcome these challenges. Convolutional neural networks (CNNs) can automatically extract relevant features and classify images into different categories, aiding in early diagnosis and intervention. It also offers a promising avenue for improving DR screening, particularly in areas with limited access to ophthalmologists. This paper aims to enhance DR grading performance by implementing a hardware solution using Raspberry Pi. One significant advantage of this approach is the potential for costeffective and portable screening in resource-limited settings. By leveraging the Raspberry Pi’s affordability and compact form factor, healthcare providers can deploy screening systems in remote areas where access to traditional medical infrastructure is limited