Diabetic Retinopathy Detection Using OpenCV, Raspberry Pi, and React and Flask with AI- powered Analysis

Author(s)	Mr Manas Mohan Shetty, Mr. Saksham Sahay, Dr. Ragunthar T
Country	India
Abstract	Diabetic Retinopathy (DR) is a leading cause of preventable blindness, particularly in underserved regions lacking access to specialized diagnostic tools and expertise. This paper proposes a cost-effective, accessible system for DR detection, integrating OpenCV for image analysis, Raspberry Pi for localized processing, and the React and Flask for seamless data management and visualization. Utilizing publicly available retinal image datasets and AI-powered analysis, the system identifies early signs of DR, facilitating timely intervention and treatment. The proposed solution demonstrates the potential to empower healthcare providers and underserved communities, aligning with Sustainable Development Goal (SDG) 3: Good Health and Well-being. The framework combines affordability, scalability, and state-of-the-art technology, providing a significant step toward democratizing DR diagnosis and reducing the global burden of diabetic retinopathy.
Keywords	Diabetic Retinopathy Detection, React and Flask, Image Processing, Cost-effective Diagnosis, Healthcare Accessibility, Sustainable Development Goal 3
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-11-20
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.41616

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