AI-WEAR: SMART TEXT READER FOR BLIND/VISUALLY IMPAIRED STUDENTS USING RASPBERRY PI WITH AUDIO-VISUAL CALL AND GOOGLE ASSISTANCE

Main Article Content

ALLEN ATIENZA LLORCA
Mia Villar Villarica
Harrold Molinyawe Gueta
Mark Angelo Torres Mercado

Abstract

The goal of this research is to create a prototype referred to as AI-WEAR: Smart Text Reader for Blind or Visually Impaired Students, which utilizes Raspberry Pi equipped with Audio-Visual Call and Google Assistance. The prototype incorporates various functionalities including text-to-speech capability for reading, Google assistance for online support, and video streaming through Jitsi Meet, enabling students to interact with their teachers. The device offers two modes of control: voice commands and user-friendly buttons with Braille letters engraved on them. OCR (Optical Character Recognition) and Text-to-Speech are integrated into the system. Synthesis techniques on the Raspberry Pi platform. By utilizing OCR, the device scans and extracts text, which is then converted into audio output through a headset. Additionally, the device employs GSM/GPRS technology to access the internet via cellular data when Wi-Fi connectivity is unavailable. The researcher employed the Long-Short Term Memory and Image processing algorithms in this project, and extensive testing and maintenance have been conducted, resulting in favourable evaluation outcomes. The prototype has successfully met the desires of the ISO/IEC 25010 standard. Although some adjustments may be necessary, this proposed device has significant potential to provide visually impaired individuals with innovative learning opportunities, especially in distance education settings. Furthermore, a cost-comparative analysis for future mass production of this assistive prototype tool for blind and visually impaired has been conducted.

 

 

Downloads

Download data is not yet available.

Article Details

Section
Articles

References

Ahwini, G. et al., (2018). An Intelligent Virtual Assistant Using Raspberry Pi. International Journal of Current Engineering and Scientific Research (IJCESR). 5 (4).

Alon, A. et al., (2020). eyeball-PH: A Machine Vision of Assistive Philippine Bill Recognition Device for Visually Impaired. 11th IEEE Control and System Graduate Research Colloquium (ICSGRC). 312-317. DOI: 10.1109/ICSGRC49013.2020.9232557.

Alvarez et al., (2019). Tactica: An Android-Based Low-Cost Assistive Tactile Device on Basic Braille Notation Reading for Visually Impaired Students in SPED Centers with IoT Technology. Journal of Communications. DOI:10.12720/jcm.14.7.593-600.

Asfar, A. & Asfar, A. (2020). How To Using Online Meeting on Jitsi Meet Application.

Researchgate. DOI:10.13140/RG.2.2.28536.80644

Baharampour, S. (2018). Student's Body Dimensions in Relation to Classroom Furniture. Health Promotion Perspectives, 2018, 3(2), 165-174.

Bhui, N. et al. (2021). Design of an Automatic Reader for the Visually Impaired Using Raspberry Pi. Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences. 175-188. DOI: 10.1007/978-981-15-7533-4_14.

Correia, A. et al., (2020). Evaluating videoconferencing systems for the quality of the

educational experience, Distance Education.

DOI:10.1080/01587919.2020.1821607.

De La Cruz, A. et al., (2019). Optical Character Reader of a Braille Unicode System for the Blind. International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, 8(1).

Dhod, R. et al., (2016). Low-Cost GPS and GSM Based Navigational Aid for Visually Impaired People. Springer Science+Business Media New York.

Gombas J. & Csakvari, J. (2021). Experiences of individuals with blindness or visual impairment during the COVID-19 pandemic lockdown in Hungary. British Journal of Visual Impairment.1–11.DOI:10.1177/0264619621990695.

Inciong, T. & Quijano, S. (2018). Inclusion of Children with Disabilities: The Philippines Experience. Asia Pacific Journal of Education. 24(2):173-191 DOI: 10.1080/02188791.2004.10600208

Khattar, S. et al., (2019). Smart Home With Virtual Assistant Using Raspberry Pi. 9th International Conference on Cloud Computing, Data Science & Engineering.

Faruque J., Vekerdy Z., Hasan Y., Islam K., Young B,. Ahmed M., Monir M., Shovon S., Kakon J., & Kundu, P. (2020) Monitoring of land use and land cover changes by using remote sensing and GIS techniques at human-induced mangrove forests areas in Bangladesh

Khormi, A. et al. (2020). A Study on the Accuracy of OCR Engines for Source Code Transcription from Programming Screencasts. 17th International Conference on Mining Software Repositories.

Malipot, M. (2020, July 3). DepEd addresses challenges in special education under ‘new normal’. Manila Bulletin.

Miah, R. & Hussain, S. (2018). A Unique Smart EyeGlass for Visually Impaired People. International Conference on Advancement in Electrical and Electronic Engineering. 22-24

Pandey, K. (2018). Comparative Study of Adjustment of Visually Impaired Students Universal Journal of Educational Research 6(11):25622571 DOI:10.13189/ujer.2018.061121.

Pascual, R. (2018). Development and Evaluation of a Scanned Filipino Text-to-Speech Device as a Reading Aid for the Blind and Visually Impaired. 14th National Natural Language Processing Research Symposium, Philippines.

Pradeep, S. et al., (2018). IoT Based Public Bus Boarding Aid for the Visually Impaired. Asian Journal of Convergence in Technology. 4 (1).

Qamar, L. (2020). Impact of COVID-19 Pandemic on Visually Impaired People with Public Media Alliance and Accessibility to Persons with Disability in India. International Journal of Policy Sciences and Law. 1(4).

Raspberry Pi Trading Ltd (2019). Automatic video processing based on IoT using Raspberry Pi. Raspberry Pi Foundation.

Sarkar, S. et al. (2021). Smart Reader for Visually Impaired Using Raspberry Pi. IOP Conference Series Materials Science and Engineering 1132(1):012032 DOI:10.1088/1757-899X/1132/1/012032.

Suitter, J. (2018). Accuracy of Optical Character Recognition Software Google Tesseract. Thinking Matters Symposium Archive. 46.

Sultan, R. & Hoque, M. ABYS (Always By Your Side): A Virtual Assistant for Visually Impaired Persons. International Conference on Computer and Information Technology (ICCIT), 18-20.

Vashistha, P. et al., (2019). Raspberry Pi-based voice-operated personal assistant (Neobot). Proceedings of the Third International Conference on Electronics Communication and Aerospace Technology.

Velmurugan, D. et al. (2018). A Smart Reader for Visually Impaired People Using Raspberry PI. International Journal of Engineering Science and Computing. 6(3). DOI 10.4010/2016.699.

Zacharias, E. et al. (2020). Image Processing Based Scene-Text Detection and Recognition with Tesseract. International Journal of Engineering & Technology. 7(2).

Hyo Geun Choi, E. et al. (2018). Visual impairment and risk of depression: A longitudinal follow-up study using a national sample cohort. International Journal of Science and Technology. Publishing Online. 8:2083 | DOI: 10.1038/s41598-018-20374-5

Daniel Jurafsky, E. et al. (2023). Speech and Language Processing. International Journal of Computer Science & Technology.