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

Yu Chen, Guo Shi, Mohammad Al-Quraan, Yusuf Sambo, Oluwakayode Onireti, Muhammad Imran

Research output: Contribution to journalArticlepeer-review


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)1-13
Number of pages13
JournalIEEE Transactions on Vehicular Technology
Early online date1 Feb 2024
Publication statusE-pub ahead of print - 1 Feb 2024


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


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