In today's society, where independent living is becoming increasingly important, it can be extremely constricting for those who are blind. Blind and visually impaired (BVI) people face challenges because they need manual support to prompt information about their environment. In this work, we took our first step towards developing an affordable and high-performing eye wearable assistive device, DRISHTI, to provide visual navigation assistance for BVI people. This system comprises a camera module, ESP32 processor, Bluetooth module, smartphone and speakers. Using artificial intelligence, this system is proposed to detect and understand the nature of the users' path and obstacles ahead of the user in that path and then inform BVI users about it via audio output to enable them to acquire directions by themselves on their journey. This first step discussed in this paper involves establishing a proof-of-concept of achieving the right balance of affordability and performance by testing an initial software integration of a currency detection algorithm on a low-cost embedded arrangement. This work will lay the foundation for our upcoming works toward achieving the goal of assisting the maximum of BVI people around the globe in moving independently.
@article{arxiv.2303.07451,
title = {DRISHTI: Visual Navigation Assistant for Visually Impaired},
author = {Malay Joshi and Aditi Shukla and Jayesh Srivastava and Manya Rastogi},
journal= {arXiv preprint arXiv:2303.07451},
year = {2023}
}
Comments
Paper presented at International Conference on Advancements and Key Challenges in Green Energy and Computing (AKGEC 2023) is accepted to be published in the proceedings of the Journal of Physics