📅 28 October 2025
DOI: 10.26877/asset.v7i4.2380
“Demata 2.0”: An On-Device AI Assistive Technology for the Visually Impaired Integrating YOLOv10 and OCR
Advance Sustainable Science, Engineering and Technology
Universitas Persatuan Guru Republik Indonesia Semarang
📄 Abstract
Accessibility to printed materials and independent recognition of the environment remain key challenges for students with visual impairments. To address this issue, this study introduces Demata 2.0, a fully offline on device multimodal AI system. The system integrates Google ML Kit for Optical Character Recognition (OCR) and the YOLOv10 model via TensorFlow Lite for object detection. A mathematical distance algorithm in the RGB color space enables color identification. Evaluation showed that object detection achieved a mean average precision of 31.83%, with an average processing speed of 2–3 FPS. For OCR, the system recorded a Character Error Rate (CER) of 4.81% and a Word Error Rate (WER) of 10.71% on printed documents. The RGB algorithm also determined the closest possible color effectively. Overall, Demata 2.0 advances assistive technology by providing an efficient and practical blueprint for AI integration.
🔖 Keywords
#assistive technology; on-device AI; optical character recognition; visual impairment; YOLOv10
ℹ️ Informasi Publikasi
Tanggal Publikasi
28 October 2025
Volume / Nomor / Tahun
Volume 7, Nomor 4, Tahun 2025
📝 HOW TO CITE
Abadi, Reza Febri; Pratama, Toni Yudha; Asmiati, Neti; Devi, Ade Anggraini Kartika; Yuwono, Joko; Dwi Setia Permana; Bahrudin, Febrian Alwan, "“Demata 2.0”: An On-Device AI Assistive Technology for the Visually Impaired Integrating YOLOv10 and OCR," Advance Sustainable Science, Engineering and Technology, vol. 7, no. 4, Oct. 2025.
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