Development of Blind Campus Navigation System with Obstacle Detection Device

Olaleye Solomon Babatunde; Adebiyi Benedictus Adekunle; Abdulsalaam Aminat; Nwosu Florence Chika; Adeyanju Abosede Olayinka; Ambi Hassana Mamman; Omolayo Clement

doi:doi:10.11648/j.ajset.20240902.12

Research Article |

| Peer-Reviewed

Development of Blind Campus Navigation System with Obstacle Detection Device

Olaleye Solomon Babatunde^*

, Adebiyi Benedictus Adekunle

, Abdulsalaam Aminat

, Nwosu Florence Chika

, Adeyanju Abosede Olayinka

, Ambi Hassana Mamman

, Omolayo Clement

Published in American Journal of Science, Engineering and Technology (Volume 9, Issue 2)

Received: 28 March 2024 Accepted: 13 April 2024 Published: 28 April 2024

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Abstract

This study focuses on integrating Text-To-Speech software, Global Positioning System (GPS) and other technologies attached to existing white cane to create a robust navigation system that provides real-time feedback and assistance to Students with Visual Impairment (SVI) using Nigerian accent. It uses the design science research methodology for the development and validation of the GPS based mobility into object detection white cane for orientation and mobility of SVI. A speech-corpus database was created to serve as a dictionary for the Text-To-Speech and synthesized through machine learning and artificial intelligence to enable the object detection white cane to detect objects and identify common places at 30 meters in Federal College of Education (Special), Oyo campus, Oyo state, Nigeria. The developed object detection white cane was evaluated with 20 SVI selected for the study using the purposive sampling technique and data were collected through interviews and questionnaires. Two research questions were raised for the study. Data collected were analyzed both quantitatively and qualitatively, using Statistical Package for the Social Sciences (SPSS) and Atlas.ti. The results revealed that the mean response of the participants to all the items on the integration of Text-To-Speech software into object detection white cane is “1” an indication that Text-To-Speech software enhances the independent navigation of students with visual impairment. The study recommended that the components used were imported and expensive, hence the need for locally source components that can be used in producing the devices in large quantities and at reduced cost.

Published in	American Journal of Science, Engineering and Technology (Volume 9, Issue 2)
DOI	10.11648/j.ajset.20240902.12
Page(s)	50-59
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Blind, Campus, Navigation System, White Cane

References

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[2]	Winifred, B. H. (1979). Speech-act and text-act theory: “Theme-ing” in Freshman composition. College Composition and Communication, 30(2), 165-169.
[3]	Kuriakose, B., Shrestha, R. & Sandnes, F. E. (2022). Tools and technologies for blind and visually impaired navigation support: A review. The Institute of Electronics and Telecommunications Engineers (IETE), 39(1), 3-18. https://doi.org/10.1080/02564602.2020.1819893
[4]	Hossain, E., Rahman, M. & Qaiduzzaman, K. M. (2020). Sightless helper: An interactive mobile application for blind assistance and safe navigation, Cyber Security and Computer Science, 1-12. https://doi.org/10.1007/978-3-030-52856-0_46
[5]	Naipal S., & Rampersad, N. (2018). A review of visual impairment. African Vision and Eye Health, 77(1), a393, 1-4. https://doi.org/10.4102/aveh.v77i1.393
[6]	Adeniran, S. & Faniran, T. S. (2022). Development of smart intelligent walking aid 3^rd eye for the blind using ultrasonic sensor. University of Ibadan Journal of Science and Logics in ICT Research, 8(2), 27-36.
[7]	Chen, Z. Liu, X. Kojima, M. Huang, Q. Arai, T. (2021). A wearable navigation device for visually impaired people based on the real-time semantic visual SLAM system. Sensors, 21, 1-13. https://doi.org/10.3390/s21041536
[8]	Innosencia, E. & Kelefa, M. (2017). ICT accessibility and usability to support learning of visually impaired students in Tanzania. International Journal of Education and Development Using ICT, 13(2), 87-102.
[9]	Saranya, M. & Nithya, K. (2015). Campus navigation and identifying current location through android device to guide blind people. International Research Journal of Engineering and Technology, 2(8), 1339-1343.
[10]	Nair, A. K. & Sahoo, J. (2021). Edge eye: A voice assisted campus navigation system for visually impaired," 2021 3rd International Conference on Signal Processing and Communication (ICPSC), Coimbatore, India, 2021, pp. 125-129, https://doi.org/10.1109/ICSPC51351.2021.9451791
[11]	Mehigan, T. J. & Pitt, I. (2012). Harnessing Wireless Technologies for Campus Navigation by Blind Students and Visitors. In: Miesenberger, K., Karshmer, A., Penaz, P., Zagler, W. (eds) Computers Helping People with Special Needs. ICCHP 2012. Lecture Notes in Computer Science, 7383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31534-3_11
[12]	Morad, A. H. (2010). GPS talking for blind people. Journal of Emerging Technologies in Web Intelligence, 2(3), 239-243. https://doi.org/10.4304/jetwi.2.3.239-243
[13]	Pawar, M., Pawar, M. & Najawan, R. (2016). Route finding application for blind people. International Journal of Engineering Development and Research, 4(2), 144-147.
[14]	Theodorou, P., Tsiligkos, K., Meliones, A., Filios, C. (2022). An extended usability and UX evaluation of a mobile application for the navigation of individuals with blindness and visual impairments outdoors—an evaluation framework based on training. Sensors. 22(12), 4538, 1-42. https://doi.org/10.3390/s22124538
[15]	See, A. R., Sasing, B. G., Advincula, W. D. (2022). A smartphone-based mobility assistant using depth imaging for visually impaired and blind. Applied Sciences. 12(6), 2802, 1-14. https://doi.org/10.3390/app12062802

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APA Style

Babatunde, O. S., Adekunle, A. B., Aminat, A., Chika, N. F., Olayinka, A. A., et al. (2024). Development of Blind Campus Navigation System with Obstacle Detection Device. American Journal of Science, Engineering and Technology, 9(2), 50-59. https://doi.org/10.11648/j.ajset.20240902.12

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ACS Style

Babatunde, O. S.; Adekunle, A. B.; Aminat, A.; Chika, N. F.; Olayinka, A. A., et al. Development of Blind Campus Navigation System with Obstacle Detection Device. Am. J. Sci. Eng. Technol. 2024, 9(2), 50-59. doi: 10.11648/j.ajset.20240902.12

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AMA Style

Babatunde OS, Adekunle AB, Aminat A, Chika NF, Olayinka AA, et al. Development of Blind Campus Navigation System with Obstacle Detection Device. Am J Sci Eng Technol. 2024;9(2):50-59. doi: 10.11648/j.ajset.20240902.12

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@article{10.11648/j.ajset.20240902.12,
  author = {Olaleye Solomon Babatunde and Adebiyi Benedictus Adekunle and Abdulsalaam Aminat and Nwosu Florence Chika and Adeyanju Abosede Olayinka and Ambi Hassana Mamman and Omolayo Clement},
  title = {Development of Blind Campus Navigation System with Obstacle Detection Device
},
  journal = {American Journal of Science, Engineering and Technology},
  volume = {9},
  number = {2},
  pages = {50-59},
  doi = {10.11648/j.ajset.20240902.12},
  url = {https://doi.org/10.11648/j.ajset.20240902.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajset.20240902.12},
  abstract = {This study focuses on integrating Text-To-Speech software, Global Positioning System (GPS) and other technologies attached to existing white cane to create a robust navigation system that provides real-time feedback and assistance to Students with Visual Impairment (SVI) using Nigerian accent. It uses the design science research methodology for the development and validation of the GPS based mobility into object detection white cane for orientation and mobility of SVI. A speech-corpus database was created to serve as a dictionary for the Text-To-Speech and synthesized through machine learning and artificial intelligence to enable the object detection white cane to detect objects and identify common places at 30 meters in Federal College of Education (Special), Oyo campus, Oyo state, Nigeria. The developed object detection white cane was evaluated with 20 SVI selected for the study using the purposive sampling technique and data were collected through interviews and questionnaires. Two research questions were raised for the study. Data collected were analyzed both quantitatively and qualitatively, using Statistical Package for the Social Sciences (SPSS) and Atlas.ti. The results revealed that the mean response of the participants to all the items on the integration of Text-To-Speech software into object detection white cane is “1” an indication that Text-To-Speech software enhances the independent navigation of students with visual impairment. The study recommended that the components used were imported and expensive, hence the need for locally source components that can be used in producing the devices in large quantities and at reduced cost.
},
 year = {2024}
}

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TY  - JOUR
T1  - Development of Blind Campus Navigation System with Obstacle Detection Device

AU  - Olaleye Solomon Babatunde
AU  - Adebiyi Benedictus Adekunle
AU  - Abdulsalaam Aminat
AU  - Nwosu Florence Chika
AU  - Adeyanju Abosede Olayinka
AU  - Ambi Hassana Mamman
AU  - Omolayo Clement
Y1  - 2024/04/28
PY  - 2024
N1  - https://doi.org/10.11648/j.ajset.20240902.12
DO  - 10.11648/j.ajset.20240902.12
T2  - American Journal of Science, Engineering and Technology
JF  - American Journal of Science, Engineering and Technology
JO  - American Journal of Science, Engineering and Technology
SP  - 50
EP  - 59
PB  - Science Publishing Group
SN  - 2578-8353
UR  - https://doi.org/10.11648/j.ajset.20240902.12
AB  - This study focuses on integrating Text-To-Speech software, Global Positioning System (GPS) and other technologies attached to existing white cane to create a robust navigation system that provides real-time feedback and assistance to Students with Visual Impairment (SVI) using Nigerian accent. It uses the design science research methodology for the development and validation of the GPS based mobility into object detection white cane for orientation and mobility of SVI. A speech-corpus database was created to serve as a dictionary for the Text-To-Speech and synthesized through machine learning and artificial intelligence to enable the object detection white cane to detect objects and identify common places at 30 meters in Federal College of Education (Special), Oyo campus, Oyo state, Nigeria. The developed object detection white cane was evaluated with 20 SVI selected for the study using the purposive sampling technique and data were collected through interviews and questionnaires. Two research questions were raised for the study. Data collected were analyzed both quantitatively and qualitatively, using Statistical Package for the Social Sciences (SPSS) and Atlas.ti. The results revealed that the mean response of the participants to all the items on the integration of Text-To-Speech software into object detection white cane is “1” an indication that Text-To-Speech software enhances the independent navigation of students with visual impairment. The study recommended that the components used were imported and expensive, hence the need for locally source components that can be used in producing the devices in large quantities and at reduced cost.

VL  - 9
IS  - 2
ER  -

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Author Information

Olaleye Solomon Babatunde

Department of Computer Science, Federal College of Education (Special), Oyo, Nigeria

Contact Email

http://orcid.org/0009-0001-1501-3328
Adebiyi Benedictus Adekunle

Department of Education for Learners with Visual Impairment, Federal College of Education (Special), Oyo, Nigeria

http://orcid.org/0009-0009-9353-1460
Abdulsalaam Aminat

Department of Computer Science, Federal College of Education (Special), Oyo, Nigeria

http://orcid.org/0000-0003-4370-3737
Nwosu Florence Chika

Department of Linguistics and Nigerian Languages, University of Ilorin, Ilorin, Nigeria

http://orcid.org/0009-0006-0531-6743
Adeyanju Abosede Olayinka

Department of Yoruba Language, Emmanuel Alayande University of Education, Oyo, Nigeria

http://orcid.org/0009-0006-0531-6743
Ambi Hassana Mamman

Department of Hausa, Federal College of Education (Special), Oyo, Nigeria

http://orcid.org/0009-0001-1331-9294
Omolayo Clement

Management Information System Unit, Federal College of Education (Special), Oyo, Nigeria

http://orcid.org/0009-0001-8878-1272

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Plain Text BibTeX RIS

APA Style

Babatunde, O. S., Adekunle, A. B., Aminat, A., Chika, N. F., Olayinka, A. A., et al. (2024). Development of Blind Campus Navigation System with Obstacle Detection Device. American Journal of Science, Engineering and Technology, 9(2), 50-59. https://doi.org/10.11648/j.ajset.20240902.12

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ACS Style

Babatunde, O. S.; Adekunle, A. B.; Aminat, A.; Chika, N. F.; Olayinka, A. A., et al. Development of Blind Campus Navigation System with Obstacle Detection Device. Am. J. Sci. Eng. Technol. 2024, 9(2), 50-59. doi: 10.11648/j.ajset.20240902.12

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AMA Style

Babatunde OS, Adekunle AB, Aminat A, Chika NF, Olayinka AA, et al. Development of Blind Campus Navigation System with Obstacle Detection Device. Am J Sci Eng Technol. 2024;9(2):50-59. doi: 10.11648/j.ajset.20240902.12

Copy | Download

@article{10.11648/j.ajset.20240902.12,
  author = {Olaleye Solomon Babatunde and Adebiyi Benedictus Adekunle and Abdulsalaam Aminat and Nwosu Florence Chika and Adeyanju Abosede Olayinka and Ambi Hassana Mamman and Omolayo Clement},
  title = {Development of Blind Campus Navigation System with Obstacle Detection Device
},
  journal = {American Journal of Science, Engineering and Technology},
  volume = {9},
  number = {2},
  pages = {50-59},
  doi = {10.11648/j.ajset.20240902.12},
  url = {https://doi.org/10.11648/j.ajset.20240902.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajset.20240902.12},
  abstract = {This study focuses on integrating Text-To-Speech software, Global Positioning System (GPS) and other technologies attached to existing white cane to create a robust navigation system that provides real-time feedback and assistance to Students with Visual Impairment (SVI) using Nigerian accent. It uses the design science research methodology for the development and validation of the GPS based mobility into object detection white cane for orientation and mobility of SVI. A speech-corpus database was created to serve as a dictionary for the Text-To-Speech and synthesized through machine learning and artificial intelligence to enable the object detection white cane to detect objects and identify common places at 30 meters in Federal College of Education (Special), Oyo campus, Oyo state, Nigeria. The developed object detection white cane was evaluated with 20 SVI selected for the study using the purposive sampling technique and data were collected through interviews and questionnaires. Two research questions were raised for the study. Data collected were analyzed both quantitatively and qualitatively, using Statistical Package for the Social Sciences (SPSS) and Atlas.ti. The results revealed that the mean response of the participants to all the items on the integration of Text-To-Speech software into object detection white cane is “1” an indication that Text-To-Speech software enhances the independent navigation of students with visual impairment. The study recommended that the components used were imported and expensive, hence the need for locally source components that can be used in producing the devices in large quantities and at reduced cost.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Development of Blind Campus Navigation System with Obstacle Detection Device

AU  - Olaleye Solomon Babatunde
AU  - Adebiyi Benedictus Adekunle
AU  - Abdulsalaam Aminat
AU  - Nwosu Florence Chika
AU  - Adeyanju Abosede Olayinka
AU  - Ambi Hassana Mamman
AU  - Omolayo Clement
Y1  - 2024/04/28
PY  - 2024
N1  - https://doi.org/10.11648/j.ajset.20240902.12
DO  - 10.11648/j.ajset.20240902.12
T2  - American Journal of Science, Engineering and Technology
JF  - American Journal of Science, Engineering and Technology
JO  - American Journal of Science, Engineering and Technology
SP  - 50
EP  - 59
PB  - Science Publishing Group
SN  - 2578-8353
UR  - https://doi.org/10.11648/j.ajset.20240902.12
AB  - This study focuses on integrating Text-To-Speech software, Global Positioning System (GPS) and other technologies attached to existing white cane to create a robust navigation system that provides real-time feedback and assistance to Students with Visual Impairment (SVI) using Nigerian accent. It uses the design science research methodology for the development and validation of the GPS based mobility into object detection white cane for orientation and mobility of SVI. A speech-corpus database was created to serve as a dictionary for the Text-To-Speech and synthesized through machine learning and artificial intelligence to enable the object detection white cane to detect objects and identify common places at 30 meters in Federal College of Education (Special), Oyo campus, Oyo state, Nigeria. The developed object detection white cane was evaluated with 20 SVI selected for the study using the purposive sampling technique and data were collected through interviews and questionnaires. Two research questions were raised for the study. Data collected were analyzed both quantitatively and qualitatively, using Statistical Package for the Social Sciences (SPSS) and Atlas.ti. The results revealed that the mean response of the participants to all the items on the integration of Text-To-Speech software into object detection white cane is “1” an indication that Text-To-Speech software enhances the independent navigation of students with visual impairment. The study recommended that the components used were imported and expensive, hence the need for locally source components that can be used in producing the devices in large quantities and at reduced cost.

VL  - 9
IS  - 2
ER  -

Copy | Download