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Indoor Positioning System (IPS) Using Ultra-Wide Bandwidth (UWB)-For Industrial Internet of Things (IIoT).
Che, Fuhu; Ahmed, Qasim Zeeshan; Lazaridis, Pavlos I; Sureephong, Pradorn; Alade, Temitope.
Afiliación
  • Che F; Department of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK.
  • Ahmed QZ; Department of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK.
  • Lazaridis PI; Department of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK.
  • Sureephong P; College of Arts, Media and Technology, Chiang Mai University, Chiang Mai 50200, Thailand.
  • Alade T; Department of Computer Science, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.
Sensors (Basel) ; 23(12)2023 Jun 19.
Article en En | MEDLINE | ID: mdl-37420883
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Internet de las Cosas Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Internet de las Cosas Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article