Muhammad Ihsanul Raihan, . (2025) RANCANG BANGUN ALAT KLASIFIKASI TABLET OBAT PANADOL, PROCOLD FLU, DAN OMEPRAZOLE BERBASIS CNN UNTUK TUNANETRA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Visual impairment poses a significant challenge for the visually impaired in independently identifying medications, risking incorrect drug usage. This research aims to design and develop a medicine tablet detection device for the visually impaired that can autonomously recognize three common types of tablets (Omeprazole, Panadol, and Procold Flu) with audio output. The device utilizes a Convolutional Neural Network (CNN) with a VGG-16 architecture implemented on a local server and integrated with an ESP32-WROVER-CAM microcontroller for image processing and a DFPlayer Mini MP3 module for the audio interface. The training dataset consisted of 1500 images, augmented from 186 original images per class. Testing results on 90 samples showed a system accuracy of 96.67%, with detailed results of 100% for Omeprazole, 100% for Panadol, and 90% for Procold Flu. The findings prove that the developed device can effectively assist the visually impaired in accurately, quickly, and independently identifying medicine tablets through audio feedback.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Audio Output, Convolutional Neural Network (CNN), ESP32-CAM, Medicine Classification, VGG-16, Visually Impaired. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Teknik > Program Studi Teknik Elektro (S1) |
| Depositing User: | MUHAMMAD IHSANUL RAIHAN |
| Date Deposited: | 03 Mar 2026 03:24 |
| Last Modified: | 03 Mar 2026 03:24 |
| URI: | http://repository.upnvj.ac.id/id/eprint/49426 |
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