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LoRa Mesh-5G Integrated Network for Trackside Smart Weather Monitoring

  • Yu Chen
  • , Guo Shi
  • , Mohammad Al-Quraan
  • , Yusuf Sambo
  • , Oluwakayode Onireti
  • , Muhammad Imran
  • University of Glasgow
  • University of Strathclyde

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Monitoring of trackside weather is a critical aspect of railway operations, mainly for safety and efficiency reasons. Unfortunately, current cellular networks, including the fourth-generation and fifth-generation (5G) cellular networks, do not provide ubiquitous coverage for rail lines mainly due to an unfavorable cost-benefit realization. In this paper, we propose a Long Range (LoRa) mesh-5G integrated network that tackles this problem by utilizing a 5G network for backhaul, computing and storage, and LoRa mesh to extend coverage. We design a LoRa mesh server that runs on a private cloud of the 5G network to manage the LoRa mesh network. We integrate edge computing into the network and design a cloud-edge-terminal collaborative architecture with three algorithms for timely significant-change updates, packet loss detection, and adaptive thresholds to reduce the packet rate and data volume of the network. We validate the design by implementing a proof-of-concept on the 5G testbed at the University of Glasgow. The experimental results demonstrate the feasibility of the network and the cloud-edge-terminal collaborative architecture.

Original languageEnglish
Pages (from-to)8903-8914
Number of pages12
JournalIEEE Transactions on Vehicular Technology
Volume73
Issue number6
DOIs
StatePublished - 1 Jun 2024
Externally publishedYes

Keywords

  • 5G
  • LoRa mesh
  • cloud-edge-terminal collaboration
  • hybrid network
  • railway digitalization
  • weather monitoring

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