As individuals age, challenges such as declining vision and memory can increase the risk of medication errors, particularly among the elderly and visually impaired. To address this issue, this research presents a deep learning-based Android application for accurate and accessible drug pill recognition. The system leverages a contrast-enhanced Convolutional Neural Network (CNN) trained on a diverse pill image dataset, achieving a test accuracy of 98%. Integrated with a REST API, the model enables real-time image classification via a smartphone camera. The application further enhances usability through voice-assisted feedback and visual pill details, promoting autonomy and medication adherence. This AI-driven solution bridges the gap between healthcare and technology, offering a practical tool to reduce medication errors and improve the quality of life for users with visual and cognitive impairments.
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R Rashmi
Manipal Academy of Higher Education
Mahendra Handore Shubhangi
i-manager s Journal on Mobile Applications and Technologies
Trinity College
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Rashmi et al. (Wed,) studied this question.
synapsesocial.com/papers/68c1bd4254b1d3bfb60eeb09 — DOI: https://doi.org/10.26634/jmt.12.1.22104