<![CDATA[Limited access to visual information is a major problem faced by visually impaired individuals, making it difficult to recognize surrounding objects and identify currency denominations independently. This issue highlights the need for a system capable of presenting visual information in a more accessible form. Therefore, this study aimed to develop a real-time object detection system based on a web platform with audio output to improve accessibility. The method included requirement analysis, system design, implementation using digital image processing and deep learning techniques, and system testing. The model applied a detection confidence threshold of ≥ 70% and achieved recognition accuracy of ≥ 85% under normal conditions. The system was also integrated with text-to-speech technology to deliver detection results in audio form. The results indicated that the system operated effectively in real-time with good responsiveness through a web browser without requiring additional installation. Therefore, the developed system proved capable of enhancing accessibility and supporting the independence of visually impaired users.]]>
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