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

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 12; p. 5710
• Main Authors: Che, Fuhu, Ahmed, Qasim Zeeshan, Lazaridis, Pavlos I., Sureephong, Pradorn, Alade, Temitope
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 19.06.2023; MDPI
• Subjects: Accuracy; Algorithms; Communication; Data mining; indoor positioning system; Industrial Internet of Things; Internet of Things; Localization; machine learning; NLoS; Radio frequency; Shopping; Technology; Unmanned aerial vehicles; UWB; Wireless access points; Wireless communications; Wireless Technology; localization; UWB; indoor positioning system; machine learning; NLoS
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23125710

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.