Learning at Your Fingertips: An Innovative IoT-Based AI-Powered Braille Learning System

Abstract

Visual impairment should not hinder an individual from achieving their aspirations, nor should it be a hindrance to their contributions to society. The age in which persons with disabilities were treated unfairly is long gone, and individuals with disabilities are productive members of society nowadays, especially when they receive the right education and are given the right tools to succeed. Thus, it is imperative to integrate the latest technologies into devices and software that could assist persons with disabilities. The Internet of Things (IoT), artificial intelligence (AI), and Deep Learning (ML)/deep learning (DL) are technologies that have gained momentum over the past decade and could be integrated to assist persons with disabilities—visually impaired individuals. In this paper, we propose an IoT-based system that can fit on the ring finger and can simulate the real-life experience of a visually impaired person. The system can learn and translate Arabic and English braille into audio using deep learning techniques enhanced with transfer learning. The system is developed to assist both visually impaired individuals and their family members in learning braille through the use of the ring-based device, which captures a braille image using an embedded camera, recognizes it, and translates it into audio. The recognition of the captured braille image is achieved through a transfer learning-based Convolutional Neural Network (CNN).

Keywords

• braille learning
• education for the blind
• internet of things (IoT)
• deep learning
• smart device
• convolutional neural networks