New gEneration of adaptable Wireless sensor NEtwork for way side objeCTs in rAilway enviRonments (NEWNECTAR), a laboratory demonstrator for optimized data collection process in rail - Université Gustave Eiffel Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

New gEneration of adaptable Wireless sensor NEtwork for way side objeCTs in rAilway enviRonments (NEWNECTAR), a laboratory demonstrator for optimized data collection process in rail

Résumé

The development of networking and wireless technologies has opened the gates to the deployment of various types of Wireless Sensor Networks (WSNs) in the railway sector, allowing numerous distributed sensors to be networked to constantly monitor both fixed and moving objects in the railway systems. The wireless sensor nodes can be of high interest since they can be installed everywhere, organized in different domains and relying on different wireless technologies. The challenges of such solutions include resource optimization, Quality of Service (QoS), scalability, energy consumption, spectrum scarcity, etc. In this context, we have proposed a TRL4 Lab demonstrator known as NEWNECTAR. It is a low-power and resource-constrained WSN for adaptive data collection and forwarding that utilizes software-defined approaches both at the physical and higher layers. This paper will describe the principle and architecture of NEWNECTAR and provide performance results. The data collection and forwarding capability of a mobile sink node of the demonstrator known as Universal Sink Gateway (USG) is tested. The test results indicate that the USG can indeed perform the data collection operation from a desired wireless technology by switching its radio interfaces at a minimal distance that depends on the coverage range of the WSN node and the speed of train where the USG is mounted. Finally, two solutions for autonomous WSN nodes based on energy harvesting and wireless power transfer are proposed. A novel concept relying on wave focussing for electromagnetic energy harvesting and improved line of sight transfer based on retrodirective metasurfaces are introduced and evaluated.
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Dates et versions

hal-04487742 , version 1 (04-03-2024)

Identifiants

  • HAL Id : hal-04487742 , version 1

Citer

Dereje Mechal Molla, Hakim Badis, Marion Berbineau, Laurent George, Ali Sabra, et al.. New gEneration of adaptable Wireless sensor NEtwork for way side objeCTs in rAilway enviRonments (NEWNECTAR), a laboratory demonstrator for optimized data collection process in rail. 13h World Congress on Railway Research 2022, Jun 2022, Birmingham, United Kingdom. ⟨hal-04487742⟩
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