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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65474

Seat Allocation for Blind People in Public Transport

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65474

Volume:

10 |

6 |

Jun 2026

Pages:

1-9

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM65474

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.

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Authors

SGH

Shravani Ganesh Hinge

Electronics and Telecommunication

RMD Sinhgad School of Engineering

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SJ

Suchitra Jagtap

Electronics and Telecommunication

RMD Sinhgad School of Engineering

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VB

Vasundhara Baravkar

Electronics and Telecommunication

RMD Sinhgad School of Engineering

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SG

Sushma Gore

Electronics and Telecommunication

RMD Sinhgad School of Engineering

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Abstract

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

CV + NLP pipeline

Cite This Article

Shravani Ganesh Hinge, Suchitra Jagtap, Vasundhara Baravkar, Sushma Gore, "Seat Allocation for Blind People in Public Transport," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-9, Jun 2026. https://doi.org/10.55041/IJSREM65474

Full Article/Conclusion

  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.

References

 [1]      Rayle, L., Dai, D., Chan, N., et al. “Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco,” Transport Policy, vol. 45, pp. 168–178, 2016.  [2]       Rayhan, A., Kinzler, R., and Rayhan, R. “Natural        Language        Processing: Transforming How Machines Understand Human Language,” Conference on Artificial General Intelligence Development, 2023. DOI: [10.13140/RG.2.2.34900.99200]   [3]      Rahman, M. A., Siddika, S., Al-Baky, M. A., and Mia, M. J. “An automated navigation system for blind people,” Bulletin of Electrical Engineering and Informatics, vol. 11, no. 1, pp. 3452–3462, Jan. 2022. DOI: [10.11591/eei.v11i1.3452] [4]      Naveen Kumar, K., Sharma, S., Abraham,I. M., and Priya, S. S. “Blind assistance system using machine learning,” Hindustan Institute of Technology and Science, 2022. (Conference proceedings; details may need confirmation)  [5]      Sáez, Y., Muñoz, J., Canto, F., García, A., and Montes, H. “Assisting visually impaired people in the public transport system through RF-communication and embedded systems,” Sensors, vol. 19, no. 6, p. 1282, Mar. 2019. DOI: [10.3390/s19061282]  [6]        Kumar, G. V. S., Abhijit, C. S. S., and Sirisha, B. L. “IoT-based full duplex smart Braille system for blind and deaf,” JETIR, vol. 7, no. 2, 2020.  [7]      Almoshaogeh, M., Jamal, A., Ahmed, T., Alharbi, F., Iqbal, M., Haider, H., and Alinizi,M. “A review on disability-inclusive public transportation: Current barriers and prospects,” IEEE Access, vol. 13, pp. 75769–75790, Apr.     2025.   DOI: [10.1109/ACCESS.2025.3564225]   [8]        Khan, S., Nazir, S., and Khan, H. U. “Analysis of navigation assistants for blind and visually impaired people: A systematic review,” IEEE Access, vol. 9, pp. 26712–26735, Jan. 2021. DOI: [10.1109/ACCESS.2021.3052415]  [9]      Al Kalbani, J., Suwailam, R. B., Al Yafai, A., Al Abri, D., and Awadalla, M. “Bus detection system for blind people using RFID,” Proc. IEEE 8th GCC Conference & Exhibition, Muscat, Oman, Feb. 2015, pp. 1–6. DOI: [10.1109/IEEEGCC.2015.7060038]  [10]        Martínez-Cruz, S., Morales-Hernández,L. A., Pérez-Soto, G. I., Benitez-Rangel, J. P., and Camarillo-Gómez, K. A. “An outdoor navigation assistance system for visually impaired people in public transportation,” IEEE Access, vol. 9, pp. 130767–130777,Sept. 2021.

Editorial & Review Transparency

Publication Date

6/25/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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