Proceedings of the Multimedia University Engineering Conference (MECON 2022)

<Previous Article In Volume
Next Article In Volume>

A Fast and Precise Indoor Positioning System Based on Deep Embedded Clustering

Authors
Hui Wen Khoo1, Yin Hoe Ng1, *, Chee Keong Tan2
1Faculty of Engineering, Multimedia University, 63100, Cyberjaya, Malaysia
2School of Information Technology, Monash University Malaysia, 47500, Subang Jaya, Malaysia
*Corresponding author. Email: yhng@mmu.edu.my
Corresponding Author
Yin Hoe Ng
Available Online 23 December 2022.
DOI
10.2991/978-94-6463-082-4_6How to use a DOI?
Keywords
Indoor positioning; BLE fingerprint; deep embedded clustering
Abstract

In indoor positioning, the real-world scenario often involves a multi-floor indoor environment, resulting in the construction of a large Bluetooth low energy (BLE) fingerprint database. Subsequently, high computational complexity and increased computational time are usually associated with such a large scale indoor environment. To circumvent this issue, a clustering-based indoor positioning system (IPS) known as DECIPS is proposed in this paper to reduce the computational complexity and execution time required by the localization algorithm for location prediction. The proposed DECIPS leverages on deep embedded clustering (DEC) algorithm to group the dataset into several subsets before using them to train separate classifiers and regressors specifically customized to handle only data from one cluster. Subsequently, the performance of DECIPS is benchmarked against several state-of-the-art clustering-based IPSs. Numerical results demonstrate that DECIPS is capable of outperforming the existing clustering-based IPSs in terms of average positioning error and execution time.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the Multimedia University Engineering Conference (MECON 2022)
Series
Advances in Engineering Research
Publication Date
23 December 2022
ISBN
978-94-6463-082-4
ISSN
2352-5401
DOI
10.2991/978-94-6463-082-4_6How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Hui Wen Khoo
AU  - Yin Hoe Ng
AU  - Chee Keong Tan
PY  - 2022
DA  - 2022/12/23
TI  - A Fast and Precise Indoor Positioning System Based on Deep Embedded Clustering
BT  - Proceedings of the Multimedia University Engineering Conference (MECON 2022)
PB  - Atlantis Press
SP  - 38
EP  - 48
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-082-4_6
DO  - 10.2991/978-94-6463-082-4_6
ID  - Khoo2022
ER  -