Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Navigating
through a campus to access various services provided by its departments, is
challenging for visitors and students who are new to the university. It would
be beneficial for visitors, students, and staff to get information of all
locations that provide a specific service along with availability of each
location. People who require services from a university could also benefit from
a personalized recommendation service that makes suggestions for any questions
they have regarding services provided by the university. This research aims to
develop an easily accessible, voice-based internal navigation and crowd
management system for universities. The researchers propose to use Bluetooth
beacons for accurately identifying the location of a user, using the AR
technology for a much more interactive way of navigating users, object
detection methodologies for producing crowd density information, and using NLP
for making personalized recommendations for any questions the user might have
regarding a certain service.
Country : Sri Lanka
IRJIET, Volume 7, Issue 11, November 2023 pp. 444-452
|
[1] |
S.
Kaisler, W. Money, P. Cohen and R. C. Pant, "A decision framework for
selecting the best smartphone indoor navigation app," Decision
Support Systems, vol. 55, no. 1, pp. 1-10, 2013. |
|
[2] |
S. Lee, J.
Kim and W. Lee, "Design and implementation of an indoor navigation
system for the visually impaired," Sensors, vol. 17, no. 11,
2017. |
|
[3] |
Y. Song,
Y. Yang and P. Cheng, "The Investigation of Adoption of Voice-User
Interface (VUI) in Smart Home Systems among Chinese Older Adults," Sensors,
vol. 22, no. 4, 2022. |
|
[4] |
S. H. X.
&. C. H. Shi, "A survey of natural language processing techniques
for social media," ACM Computing Surveys, 2019. |
|
[5] |
J. Li,
"Recent Advances in End-to-End Automatic Speech Recognition," Electrical
Engineering and Systems Science, 2021. |
|
[6] |
Z. Weng,
Z. Qin, X. Tao, C. Pan, G. Liu and G. Y. Li, "Deep Learning Enabled
Semantic Communications with Speech Recognition and Synthesis," Electrical
Engineering and Systems Science, 2022. |
|
[7] |
Q. Chen,
Z. Zhuo and W. Wang, "Bert for joint intent classification and slot
filling," ArXiv, 2019. |
|
[8] |
D. Y.
Xiaofei Sun, X. Li, T. Zhang, Y. Meng, H. Qiu, G. Wang, E. Hovy and J. Li,
"Interpreting Deep Learning Models in Natural Language Processing: A
Review," arXiv, 2021. |
|
[9] |
H. Yoon,
S.-H. Park, K.-T. Lee, J. W. Park, A. K. Dey and S. Kim, "A Case Study
on Iteratively Assessing and Enhancing Wearable User Interface
Prototypes," Symmetry, vol. 9, no. 7, p. 114, 2017. |
|
[10] |
Z. Chen,
T. Ai and C. C. Kuo, "People Counting: A Comprehensive Review," IEEE
Transactions on Circuits and Systems for Video Technology, vol. 30, no.
10, pp. 3427-3452, 2019. |
|
[11] |
X. Li and
Y. Wang, "Natural Language Processing in Campus Information Systems: A
Review," Journal of Educational Technology & Society, vol.
22, no. 2, pp. 87-98, 2019. |
|
[12] |
F. Demir,
D. Kim and E. Jung, "Hey Google, Help Doing My Homework: Surveying Voice
Interactive Systems," Journal of User Experience, pp. 41-61,
2022. |
|
[13] |
S. C.
Hong, J. H. Kim and J. H. Kim, "Improving indoor navigation service for
people with visual impairments: An empirical study," Sustainability, vol.
11, no. 9, 2019. |
|
[14] |
A. Tang,
"Augmented Reality," in The Oxford Handbook of Virtuality,
Oxford University Press, 2014, pp. 237-252. |
|
[15] |
J. He, H.
Liu, Z. Guo, Y. Jiang and L. Sun, "A survey of indoor positioning
systems," Journal of Sensors, 2016. |
|
[16] |
A. B.
Garcia and R. W. Johnson, " Exploring the Feasibility of Augmented
Reality Navigation in Educational Environments," Proceedings of the
International Conference on Human-Computer Interaction, pp. 127-134,
2018. |