JCEEES

JCEEES aims to publish original articles covering the theoretical foundations of major computer, electronic and electrical engineering sciences, as well as academic, commercial and educational aspects that propose new ideas for the application and design of artificial intelligence, software and information systems. In addition to wide-ranging regular topics, JCEEES also makes it a principle to include special topics covering specific topics in all areas of interest mainly in computational medicine, artificial intelligence, computer science, and electrical & electronic engineering science.

Index
Original Article
Vision assistant for visually impaired individuals
Visually impaired individuals face significant challenges in accessing environmental information, social interactions, and safety in their daily lives. This article aims to increase the independence of visually impaired individuals and simplify their daily lives using an AI-supported image and sound recognition system. The developed prototype is a pair of glasses consisting of a Raspberry Pi 4 microprocessor, integrated headphones, touch controls, and a powerful battery management system. The electronic diagram includes the integration of a camera and microprocessor. The AI algorithms developed successfully perform tasks such as object recognition, text reading, and facial recognition. The article provides a comprehensive literature review and introduces the prototype to visually impaired users. Based on the feedback from the introduction, the prototype's ease of use and effectiveness were evaluated, and improvements were made based on user feedback. The algorithms were tested for accuracy, with the prototype achieving a 78% accuracy score, close to GPT-4's 82%. Additionally, tests with 20 users resulted in an 85% user satisfaction rate.


1. Bastola, A., Enam, M. A., Bastola, A., Gluck, A., & Brinkley, J. (2023). Multi functional glasses for the blind and visually impaired: design and development. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. doi:10.1177/21695067231192450.
2. Nazim, S., Firdous, S., Shukla, V. K., & Pillai, S. R. (2023). Smart glasses: a visual assistant for the blind. Amity University Dubai.
3. Mustafa, A., Omer, A., & Mohammed, O. (2023). Intelligent Glasses for Visually Impaired People. Sudan University for Science and Technology.
4. Waisberg, E., Ong, J., Masalkhi, M., Zaman, N., Sarker, P., Lee, A.G., & Tavakkoli, A. (2023). Meta smart glasses-large language models and the future for assistive glasses for individuals with vision impairments. Eye, 38,1036-1038. doi:10.1038/s41433-023-02842-z
5. Turk, F. RNGU-NET: a novel efficient approach in segmenting tuberculosis using chest X-ray images. <em>PeerJ Comp Sci</em>, 2024,5,10. doi: 10.7717/peerj-cs.1780
6. T&uuml;rk, Fuat. (2024). Investigation of machine learning algorithms on heart disease through dominant feature detection and feature selection. <em>Signal Image Video Process</em>, 18,1-13. doi:10.1007/s11760-024-03060-0
7. Agrawal, A., Lu, J., Antol, S., Mitchell, M., Zitnick, C. L., Batra, D., &amp; Parikh, D. (2016). VQA: Visual question answering. <em>arXiv</em>, https://arxiv.org/abs/1505.00468.
8. Papers with Code. (n.d.). Visual Question Answering. Retrieved from https://paperswithcode.com/task/visual-question-answering-1
9. OrCam MyEye 2 Pro. (n.d.). Retrieved from https://www.orcam.com/en us/orcam-myeye-2-pro
10. Envision Glasses. (n.d.). Retrieved from https://www.letsenvision.com/glasses/home
11. Berry, T. (2018, February 9). Visually stunning; aira smart glasses help the blind see airport gates. CW39. Retrieved from https://cw39.com/2018/02/09/visually-stunning-aira-smart-glasses-help-the blind-see-airport-gates.
12. Wikipedia contributors. (2023, December 9). Seeing AI. In Wikipedia, The Free Encyclopedia. Retrieved from https://en.wikipedia.org/wiki/Seeing_AI.
Volume 2, Issue 2, 2024
Page : 62-66
_Footer