Brailly

Brings physical touch to important ideas and allows visually impaired people to read documents and papers via a custom-made label sticker generated through a scanning and translating application.

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Inspiration When browsing TikTok the other day, one of the videos that grabbed my attention was a blind guy talking about how he got loads of books as presents to read to his daughter, but he couldn't read them. He then talked about the process he has to go through to add braille to these books so they can be read. This got me thinking about how businesses accommodate similar issues.

What it does Brailly is computer vision and braille translation software for handheld devices used by businesses to scan text and print braille stickers. This promotes equity over equality and empowers businesses to serve new potential customers with visual impairments, making retail spaces more accessible.

How we built it Running on Python, Brailly is created with a low resource demand in mind, making it suitable for deployment on handheld and mobile devices. We utilized: Computer Vision: Optical Character Recognition (OCR) to extract text from images Braille Translation: Text-to-braille conversion algorithms to generate accurate braille representations Lightweight Architecture: Optimized for minimal processing power and memory usage to run efficiently on portable devices

Challenges we ran into OCR Accuracy: Achieving reliable text recognition across different fonts, lighting conditions, and text orientations Resource Optimization: Balancing performance with the constraint of running on low-powered handheld devices Braille Translation: Implementing accurate Grade 2 braille translation rules and handling special characters Real-time Processing: Ensuring quick scan-to-braille conversion for a smooth user experience Accomplishments that we're proud of Successfully created a working prototype that can scan and translate text to braille in real-time Achieved low resource consumption, making the software viable for affordable handheld devices Developed an accessible solution that can genuinely impact businesses and their visually impaired customers Built a practical tool that promotes inclusivity in retail and commercial environments

What we learned The complexities of braille translation systems and the importance of Grade 1 vs Grade 2 braille Computer vision optimization techniques for mobile and embedded devices The real-world challenges businesses face in making their spaces accessible How technology can bridge accessibility gaps and create more inclusive environments

What's next for Brailly Mobile App Development: Create native iOS and Android applications for wider accessibility Hardware Integration: Partner with portable braille printer manufacturers for end-to-end solutions Multi-language Support: Expand beyond English to support braille translation in multiple languages Cloud Processing: Offer optional cloud-based processing for enhanced accuracy on resource-constrained devices Business Platform: Develop a management system for businesses to track and manage their accessibility initiatives AI Enhancement: Implement machine learning to improve OCR accuracy and context-aware braille translation

Referance's “ABCs of UEB.” https://www.brailleauthority.org/ueb/abcs/abcs-ueb.html AI was used to help with planning, generating file structure, as well as code generation and setup

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