IOT-POWERED BRAILLE ACCESS: A REFRESHABLE OCR SYSTEM FOR VISUALLY IMPAIRED AND DEAF-BLIND INDEPENDENCE

• Dr. Ahmed Al-Mansoori

  Department of Electrical Engineering, Khalifa University, United Arab Emirates

  Author

• Dr. Jason Jimenez

  Department of Computer Engineering, Universidad Politécnica de Madrid, Spain

  Author

• Prof. Daniel Cladwell

  Department of Computer Science, Technical University of Munich, Germany

  Author

Visual and deaf-blind impairments present significant challenges in accessing printed information, creating a substantial barrier to education, employment, and daily independence. Traditional assistive technologies often lack real-time adaptability and comprehensive integration. This article proposes an innovative Internet of Things (IoT)-driven solution for visually impaired and deaf-blind users, combining Optical Character Recognition (OCR) with refreshable Braille displays, all facilitated by a Wireless Sensor Network (WSN). The system aims to provide seamless, real-time conversion of visual text into tactile Braille, addressing the critical need for accessible information. By leveraging the pervasive nature of IoT and the connectivity of WSNs, this technology offers a dynamic and responsive platform for navigating diverse textual environments. The refreshable Braille component overcomes the limitations of static Braille materials, enabling on-the-fly information access. This paper details the system's architecture, methodologies for OCR processing and Braille conversion, and the WSN's role in data transmission. Potential benefits include enhanced literacy, improved independence, and greater inclusion for a demographic often marginalized by inaccessible information formats.

1. Anisha, P.R., Reddy, C.K.K., Nguyen, N.G., Bhushan, M., Kumar, A., Hanafiah, M.M., 2022. Intelligent Systems and Machine Learning for Industry: Advancements, Challenges, and Practices. CRC Press.

2. Başçiftçi, F., Eldem, A., 2016. An interactive and multi-functional refreshable Braille device for the visually impaired. Displays 41, 33–41.

3. Dandanell, J., & Henriksson, A. (2021). Brailled: A Braille translation aid.

4. de Luna, R.G., 2020. A tesseract-based optical character recognition for a text-to-braille code conversion. Int. J. Adv. Sci. Eng. Inf. Technol. 10 (1), 128–136.

5. Edwards, B.J., Lewis, S., 1998. The use of technology in programs for students with visual impairments in Florida. J. Vis. Impair. Blind. 92 (5), 302–312.

6. Fichten, C.S., Asuncion, J.V., Barile, M., Ferraro, V., Wolforth, J., 2009. Accessibility of e-learning and computer and information technologies for students with visual impairments in postsecondary education. J. Vis. Impair. Blind. 103 (9), 543–557.

7. Gautam, H., & Gaur, P. (2020, December). DRISHYAM: Real-Time Text to Braille Conversion and Realisation. In 2020 IEEE 17th India Council International Conference (INDICON) (pp. 1-7). IEEE.

8. Gayathri, S., Sujathakumari, B.A., Murthy, N.S., Balabhadra, M., Joshi, N.S., Sandesh, C., 2021. Digitized Braille cell: a novel solution for visually impaired. Int. J. Inf. Technol. 13 (3), 1201–1208.

9. Gilfeather-Crowley, P., Smith, C.E., & Youtsey, S. (2011, October). Connecting visually-impaired people to friends through wireless sensor networks. In 2011 IEEE International Conference on Systems, Man, and Cybernetics (pp. 3224-3229). IEEE.

10. Hassan, K.N., Biswas, S.K., Anwar, M.S., Siam, M.S.I, & Shahnaz, C. (2019, November). A Dual-Purpose Refreshable Braille Display Based on Real Time Object Detection and Optical Character Recognition. In 2019 IEEE International Conference on Signal Processing, Information, Communication & Systems (SPICSCON) (pp. 78-81). IEEE.

11. Holanda, G.B., Souza, J.W.M., Lima, D.A., Marinho, L.B., Girão, A.M., Frota, J.B.B., Rebouças Filho, P.P., 2018. Development of OCR system on android platforms to aid reading with a refreshable braille display in real time. Measurement 120, 150–168.

12. Hsu, B.M., 2020. Braille recognition for reducing asymmetric communication between the blind and non-blind. Symmetry 12 (7), 1069.

13. Hynes, N., Jebaraj, D., Kumar, J.S., Immanuvel, S., & Sankaranarayanan, R. (2019, August). Portable electronic braille devices–An overview. In AIP Conference Proceedings (Vol. 2142, No. 1). AIP Publishing.

14. Kavedia, E.M.S., 2019. Teaching aid for visually impaired using IOT. Advance and innovative. Research 192.

15. Khandelwal, D., Chhabra, R.S., & JindaL, S.K. (2023). A Secure Medical-Iot Device for Assisting. Security Implementation in Internet of Medical Things.

16. Kumar, R.S., Sujai, K., Ajay, R. and Vishva, S., Extracting Text from Image and Braille to Speech Conversion.

17. Kumari, S., Akole, A., Angnani, P., Bhamare, Y., & Naikwadi, Z. (2020, June). Enhanced Braille Display Use of OCR and Solenoid to Improve Text to Braille Conversion. In 2020 International Conference for Emerging Technology (INCET) (pp. 1-5). IEEE.

18. Manimegala, V., Gayathri, A., Naveen, M., Neha, J., Nikil, B., & Nithyanand, C. (2021, March). IOT Based System for Empowering Differently Abled Person. In 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS) (Vol. 1, pp. 1215-1218). IEEE.

19. Martillano, D.A., Chowdhury, A.F.D., Dellosa, J.C.M., Murcia, A.A., & Mangoma, R.J.P. (2018, November). Pindots: An assistive six-dot braille cell keying device on basic notation writing for visually impaired students with IoT technology. In Proceedings of the 2018 2nd International Conference on Education and E-Learning (pp. 41-47).

20. Reddy, C.K.K., Kaza, V.S., Anisha, P.R., Khubrani, M.M., Shuaib, M., Alam, S., Ahmad, S., 2024. Optimising barrier placement for intrusion detection and prevention in WSNs. Plos one 19 (2), e0299334.

21. Russomanno, A., O’Modhrain, S., Gillespie, R.B., Rodger, M.W., 2015. Refreshing refreshable braille displays. IEEE Trans. Haptics 8 (3), 287–297.

22. Sharavana, K., Sivasubramanian, E., Arpitha, N., Gowda, M.M., & Naik, G.M. (2020). Real-Time Text to Braille and Audio Convertor.

23. Smelyakov, K., Chupryna, A., Yeremenko, D., Sakhon, A., & Polezhai, V. (2018, August). Braille character recognition based on neural networks. In 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP) (pp. 509-513). IEEE.

24. Tiwari, S., Sethia, Y., Tanwar, A., Kumar, H., & Dwivedi, R. (2022, October). An Approach to Real-Time Indian Sign Language Recognition and Braille Script Translation. In 2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) (pp. 267-274). IEEE.

25. Yoo, D.H., Baek, S.W., 2022. Developing of text translation and display devices via Braille module. Math. Stat. Eng. Appl. 71 (3), 537–547.

• pdf

All articles published by The Parthenon Frontiers and its associated journals are distributed under the terms of the Creative Commons Attribution (CC BY 4.0) International License unless otherwise stated. 

Authors retain full copyright of their published work. By submitting their manuscript, authors agree to grant The Parthenon Frontiers a non-exclusive license to publish, archive, and distribute the article worldwide. Authors are free to:

• Share their article on personal websites, institutional repositories, or social media platforms.

• Reuse their content in future works, presentations, or educational materials, provided proper citation of the original publication.