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A mobile-cloud collaborative traffic lights detector for blind navigation

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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A mobile-cloud collaborative traffic lights detector for blind navigation. / Angin, P.; Bhargava, B.; Helal, Sumi.
11th IEEE International Conference on Mobile Data Management, MDM 2010. IEEE, 2010. p. 396-401.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Angin, P, Bhargava, B & Helal, S 2010, A mobile-cloud collaborative traffic lights detector for blind navigation. in 11th IEEE International Conference on Mobile Data Management, MDM 2010. IEEE, pp. 396-401. https://doi.org/10.1109/MDM.2010.71

APA

Angin, P., Bhargava, B., & Helal, S. (2010). A mobile-cloud collaborative traffic lights detector for blind navigation. In 11th IEEE International Conference on Mobile Data Management, MDM 2010 (pp. 396-401). IEEE. https://doi.org/10.1109/MDM.2010.71

Vancouver

Angin P, Bhargava B, Helal S. A mobile-cloud collaborative traffic lights detector for blind navigation. In 11th IEEE International Conference on Mobile Data Management, MDM 2010. IEEE. 2010. p. 396-401 doi: 10.1109/MDM.2010.71

Author

Angin, P. ; Bhargava, B. ; Helal, Sumi. / A mobile-cloud collaborative traffic lights detector for blind navigation. 11th IEEE International Conference on Mobile Data Management, MDM 2010. IEEE, 2010. pp. 396-401

Bibtex

@inproceedings{6249e44c17e9405c8702c37d7923afc6,
title = "A mobile-cloud collaborative traffic lights detector for blind navigation",
abstract = "Context-awareness is a critical aspect of safe navigation, especially for the blind and visually impaired in unfamiliar environments. Existing mobile devices for contextaware navigation fall short in many cases due to their dependence on specific infrastructure requirements as well as having limited access to resources that could provide a wealth of contextual clues. In this paper, we propose a mobile-cloud collaborative approach for context-aware navigation by exploiting the computational power of resources made available by Cloud Computing providers as well as the wealth of location-specific resources available on the Internet. We propose an extensible system architecture that minimizes reliance on infrastructure, thus allowing for wide usability. We present a traffic light detector that we developed as an initial application component of the proposed system. We present preliminary results of experiments performed to test the appropriateness for the real-time nature of the application. {\textcopyright} 2010 IEEE.",
keywords = "Assistive technology, Cloud, Context-awareness, Mobile, Navigation, Visually impaired, Application components, Blind navigation, Cloud computing, Collaborative approach, Computational power, Context- awareness, Context-Aware, Extensible systems, Traffic light, Distributed computer systems, Mobile devices",
author = "P. Angin and B. Bhargava and Sumi Helal",
year = "2010",
doi = "10.1109/MDM.2010.71",
language = "English",
isbn = "9781424470754",
pages = "396--401",
booktitle = "11th IEEE International Conference on Mobile Data Management, MDM 2010",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - A mobile-cloud collaborative traffic lights detector for blind navigation

AU - Angin, P.

AU - Bhargava, B.

AU - Helal, Sumi

PY - 2010

Y1 - 2010

N2 - Context-awareness is a critical aspect of safe navigation, especially for the blind and visually impaired in unfamiliar environments. Existing mobile devices for contextaware navigation fall short in many cases due to their dependence on specific infrastructure requirements as well as having limited access to resources that could provide a wealth of contextual clues. In this paper, we propose a mobile-cloud collaborative approach for context-aware navigation by exploiting the computational power of resources made available by Cloud Computing providers as well as the wealth of location-specific resources available on the Internet. We propose an extensible system architecture that minimizes reliance on infrastructure, thus allowing for wide usability. We present a traffic light detector that we developed as an initial application component of the proposed system. We present preliminary results of experiments performed to test the appropriateness for the real-time nature of the application. © 2010 IEEE.

AB - Context-awareness is a critical aspect of safe navigation, especially for the blind and visually impaired in unfamiliar environments. Existing mobile devices for contextaware navigation fall short in many cases due to their dependence on specific infrastructure requirements as well as having limited access to resources that could provide a wealth of contextual clues. In this paper, we propose a mobile-cloud collaborative approach for context-aware navigation by exploiting the computational power of resources made available by Cloud Computing providers as well as the wealth of location-specific resources available on the Internet. We propose an extensible system architecture that minimizes reliance on infrastructure, thus allowing for wide usability. We present a traffic light detector that we developed as an initial application component of the proposed system. We present preliminary results of experiments performed to test the appropriateness for the real-time nature of the application. © 2010 IEEE.

KW - Assistive technology

KW - Cloud

KW - Context-awareness

KW - Mobile

KW - Navigation

KW - Visually impaired

KW - Application components

KW - Blind navigation

KW - Cloud computing

KW - Collaborative approach

KW - Computational power

KW - Context- awareness

KW - Context-Aware

KW - Extensible systems

KW - Traffic light

KW - Distributed computer systems

KW - Mobile devices

U2 - 10.1109/MDM.2010.71

DO - 10.1109/MDM.2010.71

M3 - Conference contribution/Paper

SN - 9781424470754

SP - 396

EP - 401

BT - 11th IEEE International Conference on Mobile Data Management, MDM 2010

PB - IEEE

ER -