Indoor Positioning System (IPS) using Ultra-Wide Bandwidth (UWB)—for Industrial Internet of Things (IIoT)

Fuhu Che; Qasim Zeeshan Ahmed; Pavlos I. Lazaridis; Pradorn Sureephong; Temitope Alade

doi:10.3390/s23125710

Indoor Positioning System (IPS) using Ultra-Wide Bandwidth (UWB)—for Industrial Internet of Things (IIoT)

Fuhu Che, Qasim Zeeshan Ahmed, Pavlos I. Lazaridis, Pradorn Sureephong, Temitope Alade

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

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Abstract

The integration of the physical and digital world has become increasingly important, and location-based services have become the most sought-after application in the field of the Internet of Things (IoT). This paper delves into the current research on ultra-wideband (UWB) indoor positioning systems (IPS). It begins by examining the most common wireless communication-based technologies for IPSs followed by a detailed explanation of UWB. Then, it presents an overview of the unique characteristics of UWB technology and the challenges still faced by the IPS implementation. Finally, the paper evaluates the advantages and limitations of using machine learning algorithms for UWB IPS.#

Corrected: 10 October 2023: https://doi.org/10.3390/s23208360

Original language	English
Article number	5710
Journal	Sensors
Volume	23
Issue number	12
DOIs	https://doi.org/10.3390/s23125710 https://doi.org/10.3390/s23208360
Publication status	Published - 19 Jun 2023

Keywords

indoor positioning system
localization
machine learning
NLoS
UWB

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10.3390/s23125710
10.3390/s23208360Licence: CC BY

sensors-23-05710-v2Final published version, 957 KBLicence: CC BY
Correction: sensors-23-08360Final published version, 192 KBLicence: CC BY

Cite this

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abstract = "The integration of the physical and digital world has become increasingly important, and location-based services have become the most sought-after application in the field of the Internet of Things (IoT). This paper delves into the current research on ultra-wideband (UWB) indoor positioning systems (IPS). It begins by examining the most common wireless communication-based technologies for IPSs followed by a detailed explanation of UWB. Then, it presents an overview of the unique characteristics of UWB technology and the challenges still faced by the IPS implementation. Finally, the paper evaluates the advantages and limitations of using machine learning algorithms for UWB IPS.#Corrected: 10 October 2023: https://doi.org/10.3390/s23208360",

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AU - Sureephong, Pradorn

AU - Alade, Temitope

N1 - An erratum is available for this article: DOI: 10.3390/s23208360 Funding Information: Part of this work is supported by the European Union through the Horizon 2020 Marie Skłlodowska-Curie Research and Innovation Staff Exchange Programme “Research Collaboration and Mobility for Beyond 5G Future Wireless Networks (RECOMBINE)” under Grant 872857.

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AB - The integration of the physical and digital world has become increasingly important, and location-based services have become the most sought-after application in the field of the Internet of Things (IoT). This paper delves into the current research on ultra-wideband (UWB) indoor positioning systems (IPS). It begins by examining the most common wireless communication-based technologies for IPSs followed by a detailed explanation of UWB. Then, it presents an overview of the unique characteristics of UWB technology and the challenges still faced by the IPS implementation. Finally, the paper evaluates the advantages and limitations of using machine learning algorithms for UWB IPS.#Corrected: 10 October 2023: https://doi.org/10.3390/s23208360

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KW - localization

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Indoor Positioning System (IPS) using Ultra-Wide Bandwidth (UWB)—for Industrial Internet of Things (IIoT)

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Keywords

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