This work focuses on the automated detection of retinal diseases such as Diabetic Retinopathy (DR) and Age-related Macular Degeneration (AMD) using MATLAB, GLCM (Gray Level Co-occurrence Matrix), and Deep Neural Networks (DNNs). Retinal images are processed through contrast enhancement, noise reduction, and segmentation techniques to extract meaningful features. GLCM is employed for texture-based feature extraction, while a deep learning model classifies the disease stages with high precision. To enhance practical usability, the system is integrated with hardware components such as Arduino,...