Distributed Strain Sensing on a Dublin Telecom Fibre: The Luas Tram Network as a Moving Calibration Source

Rapid urban growth in Dublin is placing increasing pressure on transport, construction, and environmental management, creating a need for high-resolution observations of how the city operates at both surface and subsurface levels. This study presents progress from a project exploring the use of existing telecommunication infrastructure as a large-scale urban sensing platform through Distributed Strain Sensing (DSS), which converts optical fibres into dense seismic arrays by measuring strain-rate perturbations from ground vibrations.

A pilot deployment was carried out on a dark ~80 km fibre ring crossing Dublin city centre, residential neighbourhoods, surface tram lines, and a tunnel. A FEBUS-A1 interrogator was installed at a data centre in Dublin's north side and operated for 23 days. The most stable configuration recorded ~50 km of fibre at 500 Hz sampling and 20 m gauge length over a continuous 10-day period. The array captured clear signatures of moving vehicles and rail activity. Signal quality degrades beyond ~30 km from the interrogator, reflecting attenuation, coupling, and urban noise effects typical of long fibre links.

Now we aim to use the Luas tram network as a calibrated moving load to extract quantitative information from the DSS data. The fibre intersects the Luas Red Line over a ~1.5 km section, where the uniform fleet of Alstom Citadis 401 trams (40.8 m, 3 bogies, ~41 t tare weight) provides a recurring, well-characterised seismic source. The signal also enables refined georeferencing of channel locations: tram stops are clearly identified as ~1-minute gaps in the spatio-temporal record, providing fixed spatial anchors along the fibre. Because the trams follow a fixed schedule with known geometry, they are ideal for validating the quasi-static response of buried telecom fibre to vehicular loading, characterising fibre–ground coupling along the section, and developing a workflow to estimate tram weight — and by extension passenger load — from the quasi-static strain amplitude. We plan to follow the processing pipeline — event detection, speed estimation from spatial-temporal moveout, channel-by-channel coupling correction, and absolute calibration anchored on the known tare weight — and discuss the physical assumptions underpinning weight retrieval from fibre in telecom ducts rather than bonded to the ground. Beyond passenger-load tracking, this approach establishes the Luas as an in-situ calibration standard transferable to other vehicles and fibre sections, opening a route toward distributed weight-in-motion monitoring across urban environments.