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EYES.AI: An Intelligent Assistive System for Visually Impaired Individuals Using Artificial Intelligence


EOI: 10.11242/viva-tech.01.09.41

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Citation

Minakshi Gaonkar, Mohammed Usmani, Anurag Maurya, Parth Ghodke, Viraj Bane, “EYES.AI: An Intelligent Assistive System for Visually Impaired Individuals Using Artificial Intelligence", VIVA-IJRI Volume 1, Issue 9, Article 41, pp. 1-8, 2026.Published by Artificial Intelligence And Machine Learning Engineering Department,VIVA Institute of Technology, Virar, India.

Abstract

Visually impaired individuals continue to face significant difficulties in perceiving their environment, accessing printed content, and interacting independently with digital systems. While several assistive technologies exist, many are limited to single-use functionalities or depend on costly hardware, restricting widespread adoption. This paper presents EYES.AI, an intelligent assistive system designed to provide complete voice-based interaction, enabling visually impaired users to operate the application without any physical input. The system integrates real-time object detection, optical character recognition, text-to-speech synthesis, automated task execution, and voice-driven navigation within a smartphone-based platform. EYES.AI supports essential daily activities such as reading and sending messages, shopping assistance, document understanding, and real-time environmental description using voice commands alone. By combining on-device intelligence with cloud-assisted processing, the system achieves low latency, affordability, and scalability. The paper discusses system architecture, core functionalities, performance evaluation, and comparison with existing solutions. Experimental results demonstrate that EYES.AI offers a practical, inclusive, and cost-effective assistive solution, with future work focusing on improving recognition accuracy and contextual understanding.

Keywords

- Accessibility, Artificial Intelligence, Assistive Technology, Computer Vision, Voice Interaction.

References

  1. R. G. Johnson, and M. S. Ahmed, 2019, AI and Accessibility: Technology for the Visually Impaired, MIT Press, Cambridge, MA, pp. 34–52.
  2. T. Y. Chen, 2021, “Deep Learning in Object Recognition for Assistive Technology,” Journal of AI Research and Development, vol. 8, no. 4, pp. 101–115.
  3. S. L. Gupta, and P. N. Rao, 2020, “Text-to-Speech Systems: Enhancing Accessibility for Visually Impaired Users,” in Proceedings of the International Conference on AI in Accessibility, Toronto, Canada, pp. 145–152.
  4. N. B. Patel, 2022, Advances in AI-Driven Object Detection for Assistive Technology, Elsevier, New York, pp. 82–101.
  5. J. M. Lee, 2023, “Bridging the Gap: The Role of AI in Assistive Devices for the Visually Impaired,” IEEE Transactions on Human-Machine Systems, vol. 54, no. 2, pp. 333–345.
  6. A. S. Kaur, and M. L. Singh, 2021, “Optical Character Recognition Techniques in Accessibility Applications,” Journal of Assistive Technology and AI, vol. 11, no. 3, pp. 214–229.
  7. F. Tanaka (Ed.), 2022, AI Solutions in Healthcare and Accessibility, Springer, Tokyo, pp. 150–168.
  8. C. H. Nguyen, 2023, “Real-Time Object Detection for Assistive Devices: Challenges and Future Prospects,” in IEEE International Symposium on Assistive Technologies, pp. 59–64.
  9. P. R. Gonzalez, 2020, “Speech Synthesis for Enhanced Accessibility: Applications and Innovations,” Computational Intelligence in Accessibility, vol. 7, no. 3, pp. 270–278.
  10. L. R. Silva, and D. M. Rojas, 2021, “AI-Enhanced Mobility Solutions for the Visually Impaired,” Journal of Digital Accessibility, vol. 6, no. 2, pp. 110–122.
  11. K. Verma, and P. Kulkarni, 2021, “Assistive Mobile Applications for Visually Impaired: A Survey,” International Journal of Advanced Research in Computer Science, vol. 12, no. 4, pp. 45–52.
  12. S. R. Mehta, 2022, “Deep Learning-Based Navigation Assistance for the Visually Impaired,” Journal of Intelligent Systems, vol. 31, no. 1, pp. 89–102.
  13. D. Kumar, and A. Sharma, 2020, “Voice-Based Assistive Technology for Blind Users,” International Conference on Emerging Technologies in Computing, pp. 210–215.
  14. Y. Nakamura, 2021, “Mobile Vision-Based Assistance for Visually Impaired Users,” IEEE Access, vol. 9, pp.134560–134571.
  15. H. Zhang, and L. Wang, 2022, “Real-Time Scene Understanding for Assistive Applications,” Journal of Computer Vision and Applications, vol. 15, no. 2, pp. 98–109.
  16. P. S. Reddy, and V. Kumar, 2021, “Depth Estimation Techniques for Obstacle Avoidance,” International Journal of Image Processing, vol. 13, no. 6, pp. 305–314.
  17. M. Torres, 2020, “Wearable Assistive Devices for the Visually Impaired,” Sensors and Smart Systems, vol. 5, no. 3, pp. 55–63.
  18. A. Banerjee, and S. Das, 2023, “AI-Based Multimodal Interaction for Accessibility,” Journal of Human-Centered AI, vol. 2, no. 1, pp. 1–15.
  19. R. Oliveira, and J. Costa, 2021, “Mobile OCR Systems for Accessibility Applications,” Pattern Recognition Letters, vol. 147, pp. 45–53.
  20. S. K. Mishra, 2022, “Survey on Assistive Technologies for the Visually Impaired,” International Journal of Engineering Research & Technology, vol. 11, no. 7, pp. 876–882.
  21. T. Anderson, 2020, “Inclusive Design and Accessibility in AI Systems,” ACM Computing Surveys, vol. 53, no.6, pp. 1–29.
    22. <
  22. J. Park, and K. Lee, 2021, “Smartphone-Based Navigation Systems for Blind Users,” IEEE Consumer Electronics Magazine, vol. 10, no. 5, pp. 24–31.
  23. P. Hernández, 2022, “Multilingual Speech Interfaces for Accessibility,” Journal of Speech Technology, vol. 18, no. 4, pp. 201–214.
  24. S. Wilson, and E. Brown, 2023, “Future Trends in Assistive Artificial Intelligence,” AI & Society, vol. 38, no.2, pp. 567–57.
  25. Naayini, P., Myakala, P. K., & Kamatala, S. (2025). AI-Powered Assistive Technologies for Visual Impairment: A Review. arXiv preprint arXiv:2501.08253.
  26. Okolo, G. I., Althobaiti, T., & Ramzan, N. (2024). Assistive Systems for Visually Impaired Persons: Challenges and Opportunities for Navigation Assistance. Sensors, 24(11), 3572.
  27. Filipova, E. (2025). Enhancing Educational Accessibility for Visually Impaired Individuals through Artificial Intelligence: Challenges and Opportunities. International Journal of Computer Applications, 186(67), 25-32.
  28. Kulkarni, S., & Thorat, S. (2025). AI-SenseVision: A Low-Cost Artificial-Intelligence-Based Robust and Real-Time Assistance for Visually Impaired People. IEEE Transactions on Human-Machine Systems, (Early Access), 1-12.
    29. /ol>