Connecting Luxembourg: RideOnTrack’s collaboration with CFL for smarter railways

Based in Luxembourg City, Luxembourg, Société Nationale des Chemins de Fer Luxembourgeois (CFL) is the national railway company of Luxembourg. CFL operates a comprehensive rail network connecting Luxembourg with neighbouring countries Belgium, France, and Germany. On these railway lines, CFL acts as a major provider of freight and passenger rail services in the region, supporting both daily commuters and international travellers.

Founded in 1946, CFL plays a central role in Luxembourg’s mobility strategy by providing reliable rail transport, multimodal mobility services, and logistics solutions. Its activities include passenger rail operations, freight transportation, infrastructure management, and station services, contributing to sustainable and efficient cross-border mobility in the Greater Region.

CFL faced a challenge in obtaining continuous and coherent insight into mobile network performance along its railway tracks in Luxembourg. To get coherent and continuous data, CFL measured the throughput of onboard WiFi and mobile networks with handheld measurement equipment. However, the results lacked a dynamic, easily accessible view. This made it difficult to efficiently analyse and compare network performance in a consistent way. As the national railway company, with strong cross‑border connections to Belgium, France and Germany, CFL needed reliable information on where connectivity issues occurred, how severe they were, and how they evolved over time.

To support Luxembourg’s mobility strategy and ensure a positive passenger experience, CFL recognised that it needed a way to collect accurate throughput onboard, radio performance and geographical data along its network, and to turn these measurements into clear visual insights through modern data processing and web applications. Without such a solution, it was difficult to systematically identify weak spots, prioritise improvements, or have structured, evidence‑based discussions about connectivity with relevant stakeholders and partners.

RideOnTrack provides CFL with the CodiTrack condition‑based monitoring platform, combining IoT edge computing with a cloud‑based analytics application to deliver continuous and structured insight into mobile network performance.

CodiTrack continuously measures outside the train using the rEdge devices, while rMobile makes it possible to carry out ad hoc measurements. These measurement tools of CodiTrack capture various network performance indicators, including signal quality metrics (such as RSSI, RSRP, RSRQ and SINR), quality of service (QoS) metrics (including packet loss and latency) and throughput metrics such as download and upload speeds. Throughput measurements are performed using iperf3, following industry standards to ensure accuracy and consistency. Comparability between the outdoor and the in-train measurements using the rMobile devices is key when debating with stakeholders whether investment in infrastructure or in rolling stock should be prioritised.

CodiTrack collects all data that covers every operational condition, including different train types, carriage levels and different types of treated glass. While CFL was previously able to perform measurements in these environments, the results were not structured in a way that allowed efficient comparison. With CodiTrack, measured data can be labelled and categorised directly within the platform, enabling clear differentiation between operational conditions and supporting consistent comparisons.

The collected data is automatically processed and transferred to the cloud, and CodiTrack visualises the data related to mobile network performance along CFL’s railway tracks across Luxembourg in real-time. The rCloud platform brings together data collected from IoT devices, geographical information linked to the rail infrastructure and operational information provided by CFL, and presents it in one accessible, real‑time view.

By using CodiTrack, CFL now has continuous, real-time visibility into how different national mobile networks perform along its railway tracks in Luxembourg. Instead of relying on scattered data results and subjective information, CFL can visualise where connectivity is strong over different train types and operational conditions, and where it must be enhanced.

The ability to label and compare data from various environments allows CFL to detect and analyse coverage gaps and performance issues objectively and with far more confidence than before. These insights from CodiTrack help CFL to prioritise where improvements are needed most and to have better-informed discussions about network management with relevant partners, such as the public mobile network operators or national authorities. The possibility of sharing a static web access to a CFL-defined dataset makes interactions more tangible for executives or for external partners.

The data clearly reflects where rolling stock attenuation blocks out mobile signal and where the signal is simply unavailable to users. Over time, this data-driven approach supports more reliable onboard connectivity for passengers, paves the way for modern and connected trackside maintenance activities, and aligns with CFL’s broader role in providing modern, connected and sustainable rail services within Luxembourg and across borders.