Currency is used almost everywhere to facilitate business. In most developing
countries, especially the ones in Africa, tangible notes are predominantly used
in everyday financial transactions. One of these countries, Ethiopia, is
believed to have one of the world highest rates of blindness (1.6%) and low
vision (3.7%). There are around 4 million visually impaired people; With 1.7
million people being in complete vision loss. Those people face a number of
challenges when they are in a bus station, in shopping centers, or anywhere
which requires the physical exchange of money. In this paper, we try to provide
a solution to this issue using AI/ML applications. We developed an Android and
IOS compatible mobile application with a model that achieved 98.9%
classification accuracy on our dataset. The application has a voice integrated
feature that tells the type of the scanned currency in Amharic, the working
language of Ethiopia. The application is developed to be easily accessible by
its users. It is build to reduce the burden of visually impaired people in
Ethiopia.

本文尝试使用人工智能 / 机器学习应用程序为视力受损人士在埃塞俄比亚的使用货币场景提供解决方案。该移动应用程序可以扫描货币并在 Amharic 语言中告知其类型，旨在减轻埃塞俄比亚视力障碍人士的负担。该模型在数据集上实现了 98.9％的分类准确率。