Real-time data in track construction: from sensors to the control centre

Since August 2025, an unusual site container has been supporting work on a roughly five-kilometre section of the comprehensive Hamburg-Berlin railway upgrade near Aumühle. Rhomberg Sersa's Q-tainer is being used there on behalf of DB InfraGO. Autonomous drones document construction progress, while sensors collect environmental data and other measurements. The information is processed on site and compared with the planned construction schedule. The aim is to identify deviations as early as possible and give project managers and site supervisors an up-to-date basis for their work.

The trial on the Hamburg-Berlin line is part of a development that Rhomberg Sersa has been pursuing for several years. Real-time data in track construction is far more than a digital add-on: it fundamentally changes how work is organised. Ralf Sommer, Head of Digital Rail Services Austria at Rhomberg Sersa Rail Group, is exploring how planning and site data can be connected more closely. The benefits begin at the planning stage, where objective, continuously collected data takes the place of subjective estimates based on experience. "Planning currently often relies on the experience of individuals," Sommer explains. "Real-time data makes it possible to plan using real, objective data." This shift enables more precise forecasts and more flexible resource management, especially when planned and actual data are compared at short intervals.

There is a further benefit: data from active construction sites can inform future projects. Systematically recording construction progress, machine movements, weather and disruptions builds a broader evidence base with each project. Planning then draws not only on personal experience but increasingly on data from work actually carried out.

From site supervision to real-time control

The benefits continue during construction. Real-time information enables teams to respond promptly to deviations before they affect schedules or quality. Automated data capture supports site monitoring and gives clients a stronger evidence base for their oversight. The Hamburg-Berlin pilot already puts this into practice: progress on noise barriers, underground cable works and other activities is recorded automatically and compared with the planned schedule. This provides a much more current picture of whether individual activities are on track.

Sensors and connected systems provide the technical foundation. Rhomberg Sersa uses modern sensing technology, including AI-assisted cameras, drones and automated image analysis. The Q-tainer brings the necessary computing power directly to the site. This mobile data centre processes information locally and provides a private 5G campus network to connect sensors and other digital applications. The underlying principle is edge computing: large volumes of data can be processed where they are generated, instead of first having to be transferred in full to a remote data centre. For sites handling video and sensor data and requiring rapid responses, this is a decisive advantage.

Site safety can benefit too. AI-assisted cameras can detect whether people are wearing the required protective equipment. The movements of vehicles and people can also be analysed to identify potential collision zones and other safety risks. Rhomberg Sersa cites helmets, high-visibility vests and the identification of routes and hazardous areas as possible applications.

Sensors, computing power and transparency: the foundations for using data

Real-time data needs intelligent analysis to deliver its full value. Artificial intelligence can recognise the processes and activities of heavy equipment and automatically derive information about construction sequences, progress and resource use. Combining different sources turns individual measurements into a picture of the site. Drones supply images, sensors report operating conditions and environmental measurements, and construction schedules and BIM define the intended state. AI-assisted analysis can identify deviations and present the results to project participants through dashboards.

Sommer sees this as a fundamental shift in collaboration: "Real-time data creates transparency because everyone has the same information. Transparency usually creates trust." A shared foundation of data strengthens collaboration throughout planning, construction and maintenance. This is particularly relevant to infrastructure projects involving clients, site supervisors, contractors and numerous subcontractors. Participants often use different systems and work with different versions of information. Shared, current data does not automatically prevent disputes, but it can ensure that everyone is at least discussing the same actual conditions.

At the same time, this volume of data places high demands on IT infrastructure. Reliable networks need to be backed by decentralised computing capacity that is ready for use on site. The Q-tainer illustrates how modern infrastructure projects are building their own digital ecosystems. Its purpose is not to create another data silo. Its modular design allows different sources and applications to be integrated, so that sensor readings, imagery and other site data can be processed within a shared infrastructure.

From data streams to a production control centre

Rhomberg Sersa has a clear vision for the future: a "Rail Production Control Centre". It would connect BIM, site data, AI and digital twins to show both what is happening on site and how actual conditions differ from the planned sequence. Part of that vision is already a reality in early 2026. The Q-tainer is being used for automated progress checks and environmental monitoring during the comprehensive Hamburg-Berlin upgrade. Prompt comparisons between planned and actual data are intended to reveal deviations and allow those responsible to take corrective action early.

This is still some way from an autonomously controlled construction site. The systems supply data, recognise patterns and support decisions. The people responsible still decide whether to change a construction sequence, deploy more staff or adjust a deadline. Digitalisation does not transfer responsibility to machines; it changes the information on which decisions are based. Over time, this creates a feedback loop: the digital model describes the intended state, sensors and reality capture record actual conditions, software identifies differences, and project managers respond. Experience from the site then feeds back into future planning.

For track construction, this would be a fundamental change. BIM would no longer primarily organise planning and document the finished structure. The model would become part of an ongoing production system that continuously connects planning and site activities. In early 2026, the Rail Production Control Centre remains a vision, but its technical building blocks are already in use on site.