  The prevalence of mobile technology offers unique opportunities for
addressing healthcare challenges, especially for individuals with visual
impairments. This paper explores the development and implementation of a deep
learning-based mobile application designed to assist blind and visually
impaired individuals in real-time pill identification. Utilizing the YOLO
framework, the application aims to accurately recognize and differentiate
between various pill types through real-time image processing on mobile
devices. The system incorporates Text-to- Speech (TTS) to provide immediate
auditory feedback, enhancing usability and independence for visually impaired
users. Our study evaluates the application's effectiveness in terms of
detection accuracy and user experience, highlighting its potential to improve
medication management and safety among the visually impaired community.
Keywords-Deep Learning; YOLO Framework; Mobile Application; Visual Impairment;
Pill Identification; Healthcare
