International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI Powered Wearable Assistance Device for Visually Impaired |
|---|---|
| ABSTRACT | Visually impaired individuals face challenges navigating indoor spaces, as obstacles like people, furniture, doors, and electronic devices are not easily perceived. Traditional aids, such as white canes, provide limited feedback and do not describe objects ahead. This project presents an assistive navigation system that performs real-time object detection and provides voice guidance to alert users of obstacles in their path. A custom decision engine evaluates the spatial position of detected objects within a defined danger zone, ensuring that only relevant hazards trigger audio alerts like “Person ahead” or “Obstacle ahead.” Timing control prevents repetitive messages while maintaining real-time responsiveness. Implemented in Python with modular detection, decision-making, and voice components, the system was tested in classrooms and corridors under varying distances and lighting conditions. Results indicate that the system can reliably detect obstacles and provide timely audio cues, supporting safer short-range indoor navigation for visually impaired users. |
| AUTHOR | PROF. D.C.PARDESHI, MRUNAL BHOSALE, TANISHKA GAIKWAD, AARYA TAWARE, VED TUPE Guide, Department of Artificial Intelligence & Machine Learning, AISSMS’s Polytechnic, Pune, Maharashtra, India Department of Artificial Intelligence & Machine Learning, AISSMS's Polytechnic, Pune, Maharashtra, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401075 |
| pdf/75_AI Powered Wearable Assistance Device for Visually Impaired.pdf | |
| KEYWORDS | |
| References | [1] B. M., Logesh M., N. Kumar V., S. Prasath, and N. Saranraj, “The Virtual Assistant: A Wearable Device for Independent Living of the Visually Impaired,” International Journal of Research in Technology and Innovation, 2023. [Online]. Available: https://ijrti.org/papers/IJRTI2303055.pdf [2] D. D. Brilli, E. Georgaras, S. Tsilivaki, N. Melanitis, and K. Nikita, “AIris: An AI-powered Wearable Assistive Device for the Visually Impaired,” arXiv preprint arXiv:2405.07606v2, 9 Aug 2024. [Online]. Available: https://arxiv.org/html/2405.07606v1 [3] M. S. A. Baiga, S. A. Gillani, S. M. Shah, M. Aljawarneh, A. A. Khand, and M. H. Siddiqui, “AI-based Wearable Vision Assistance System for the Visually Impaired: Integrating Real-Time Object Recognition and Contextual Understanding Using Large Vision-Language Models,” arXiv preprint arXiv:2412.20059, 2024. [Online]. Available: https://arxiv.org/pdf/2412.20059. [4] K. P. Venkat Vivek, J. Vandana, K. Sripooja, and A. Choubey, “A Smart Wearable Guiding Device for The Visually Impaired People,” International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022. DOI: https://doi.org/10.22214/ijraset.2022.44153 |
