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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65474
Volume:
10 |
6 |
Jun 2026
Pages:
1-9
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Electronics and Telecommunication
RMD Sinhgad School of Engineering
Electronics and Telecommunication
RMD Sinhgad School of Engineering
Electronics and Telecommunication
RMD Sinhgad School of Engineering
Electronics and Telecommunication
RMD Sinhgad School of Engineering
This work proposes an end-to-end assistive system that uses computer vision (CV) and natural language processing (NLP) to locate, reserve, and guide blind or low-vision users to appropriate seats in public places (buses, trains, waiting rooms, theatres, lecture halls). The system combines real-time visual seat/occupancy detection, OCR of signage, spatial mapping (depth/pose), speech-based user interaction (intent recognition + dialog), and audio/haptic guidance. Key goals are high reliability in crowded, variable lighting conditions; low-latency on-device inference; privacy-preserving operation; and compliance with accessibility regulations. We describe related work, datasets, models, system architecture, implementation details, evaluation metrics, deployment options, ethical/privacy considerations, limitations, and a roadmap for validation.
KEYWORDS
This integrated CV + NLP system can materially improve independence and dignity for blind people navigating public places by automatically finding, reserving, and guiding them to appropriate seats. Key success factors are robust perception in crowded, varied conditions; fast, noise-robust speech understanding; privacy-first deployment; and extensive user-centered design and testing with the blind community.
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Publication Date
6/25/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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