Brahim El Boudani
Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap
El Boudani, Brahim; Dagiuklas, Tasos; Kanaris, Loizos; Iqbal, Muddesar; Chrysoulas, Christos
Authors
Tasos Dagiuklas
Loizos Kanaris
Muddesar Iqbal
Dr Christos Chrysoulas C.Chrysoulas@napier.ac.uk
Lecturer
Abstract
Indoor positioning is a core enabler for various 5G identity and context-aware applications requiring precise and real-time simultaneous localisation and mapping (SLAM). In this work, we propose a K-nearest neighbours and deep neural network (K-DNN) algorithm to improve 3D indoor positioning. Our implementation uses a novel data-augmentation concept for the received signal strength (RSS)-based fingerprint technique to produce a 3D fused hybrid. In the offline phase, a machine learning (ML) approach is used to train a model on a radiomap dataset that is collected during the offline phase. The proposed algorithm is implemented on the constructed hybrid multi-layered radiomap to improve the 3D localisation accuracy. In our implementation, the proposed approach is based on the fusion of the prominent 5G IoT signals of Bluetooth Low Energy (BLE) and the ubiquitous WLAN. As a result, we achieved a 91% classification accuracy in 1D and a submeter accuracy in 2D.
Citation
El Boudani, B., Dagiuklas, T., Kanaris, L., Iqbal, M., & Chrysoulas, C. (2023). Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap. Electronics, 12(19), Article 4150. https://doi.org/10.3390/electronics12194150
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 29, 2023 |
Online Publication Date | Oct 5, 2023 |
Publication Date | 2023 |
Deposit Date | Oct 31, 2023 |
Publicly Available Date | Oct 31, 2023 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 12 |
Issue | 19 |
Article Number | 4150 |
DOI | https://doi.org/10.3390/electronics12194150 |
Keywords | indoor localisation, 5G IoT, deep learning, machine learning, information fusion, tracking, Internet of Things |
Public URL | http://researchrepository.napier.ac.uk/Output/3214850 |
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Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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