Positioning as Service for 5G IoT Networks

Brahim El boudani, Christos Chrysoulas, Anastasios Dagiuklas

Research output: Contribution to conferencePaper

Abstract

Big Data and Artificial Intelligence are new tech- nologies to improve indoor localization. It focuses on the use of machine learning probabilistic algorithms to extract, model and analyse live and historical signal data obtained from several sources. In this respect, the data generated by 5G network and the Internet of Things is quintessential for precise indoor positioning in complex building environments. In this paper, we present a new architecture for assets and personnel location management in 5G network with an emphasis on vertical sectors in smart cities. Moreover, we explain how Big Data and Machine learning can be used to offer positioning as service. Additionally, we implement a new deep learning model for 3D positioning using the proposed architecture. The performance of the proposed model is compared against other Machine Learning algorithms.
Original languageEnglish
Publication statusPublished - 11 Feb 2021
Event2021 Telecoms Conference (ConfTELE) -
Duration: 2 Nov 2021 → …

Conference

Conference2021 Telecoms Conference (ConfTELE)
Period2/11/21 → …

Keywords

  • Big data
  • Deep learning
  • Internet of Things
  • RSS
  • 5G
  • Radiomap
  • Indoor Positioning

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