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

该研究探讨了一种基于深度学习的移动应用的开发和实施，旨在通过移动设备上的实时图像处理准确识别和区分不同类型的药丸以协助盲人和视障人士，该应用利用文本转语音（TTS）提供即时的听觉反馈，提高了视障用户的可用性和独立性。研究评估了应用的检测准确性和用户体验，凸显其在改善视障人士社区的药物管理和安全方面的潜力。