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IN2SMART2 · Project

Smart Predictive Maintenance System That Tells Railways What to Fix Before It Breaks

transportPilotedTRL 7
projects.shift2rail.org

Imagine if your railway tracks, bridges, and metro systems could tell you exactly when something is about to break — like a check-engine light for an entire rail network. That's what IN2SMART2 built: a set of intelligent monitoring tools that watch rail assets around the clock, spot problems early, and recommend when and how to fix them. They even created digital twins — virtual copies of real infrastructure — so operators can simulate wear and plan repairs without disrupting service. The system was tested on real tracks in Sweden and metro lines across Europe, reaching near-deployment readiness.

By the numbers
28
consortium partners involved in development
10
countries where technology was demonstrated
11
demonstration systems built and tested
34
total deliverables produced
68%
industry partner ratio in consortium
TRL 6/7
technology readiness level achieved by key demonstrators
The business problem

What needed solving

Railway operators and infrastructure managers spend billions on maintenance, much of it reactive — fixing things after they break rather than before. Unplanned failures cause service disruptions, safety risks, and ballooning repair costs. The industry needs a way to predict failures, prioritise repairs by actual condition data, and plan maintenance without shutting down busy lines.

The solution

What was built

The project delivered 11 working demonstration systems including: a digital twin of real rail assets with automatic pattern recognition and degradation prediction; a rail fastener anomaly detection system tested on in-service trains in Sweden at TRL 6-7; an Urban Metro intelligent asset management system at TRL 6/7; a remote condition monitoring system for reducing maintenance interventions; and an integrated demonstrator that combines heterogeneous sensor inputs through a common monitoring architecture.

Audience

Who needs this

National railway infrastructure managers (e.g., Network Rail, ProRail, DB Netz)Metro and tram operators in European citiesRail technology companies looking to integrate predictive maintenance into their productsRailway maintenance contractors seeking data-driven scheduling toolsRolling stock manufacturers adding condition monitoring to their service offerings
Business applications

Who can put this to work

Railway Infrastructure Management
enterprise
Target: National or regional railway infrastructure managers

If you are a railway infrastructure manager dealing with unplanned track failures and costly emergency repairs — this project developed an Intelligent Asset Management System with digital twins and remote condition monitoring, demonstrated up to TRL 6/7 on real operational tracks. With 11 demonstration systems tested across 10 countries, the technology covers everything from rail fastener anomaly detection to bridge monitoring and maintenance planning.

Urban Transit Operations
enterprise
Target: Metro and tram network operators

If you are a metro or tram operator struggling with maintenance scheduling that disrupts passenger service — this project built an Urban Metro IAMS demonstrator up to TRL 6/7 that integrates real-time condition monitoring with decision support. The system collects data from multiple sensor types and provides tactical and operational maintenance recommendations, helping you shift from reactive to predictive maintenance.

Rail Technology and Signalling
mid-size
Target: Rail technology suppliers and system integrators

If you are a rail technology company looking to add predictive maintenance capabilities to your product portfolio — this project created a common system architecture and Conceptual Data Model that integrates heterogeneous monitoring inputs from 28 consortium partners. The open integration approach and TRL 6/7 demonstrators across track, bridges, and remote monitoring provide a proven foundation for commercial product development.

Frequently asked

Quick answers

What would it cost to implement this system on our rail network?

The project data does not include specific pricing or per-kilometer costs. However, the system was developed as an Innovation Action coordinated by Hitachi Rail STS, a major commercial rail technology provider, with 19 industry partners — suggesting commercial viability was a design priority. Contact the consortium for deployment pricing.

Can this scale to a national rail network or is it only for test sections?

The project demonstrated its systems across 10 countries on both mainline railway and metro/tram lines, including an in-service train running on Sweden's iron-ore line. The integrated demonstrator collected heterogeneous inputs from multiple vertical demonstrators, showing the architecture can handle network-scale deployment.

Who owns the intellectual property and can we license the technology?

The project was coordinated by Hitachi Rail STS SPA with 28 partners across 10 countries. IP ownership is distributed among consortium members according to their Shift2Rail participation agreements. Licensing discussions should be directed to specific technology owners within the consortium, starting with the coordinator.

How mature is this technology — is it ready for deployment?

Multiple demonstrators reached TRL 6/7, meaning they were validated in relevant operational environments. The rail fastener anomaly detection system, the Urban Metro IAMS, and the Remote Condition Monitoring system all demonstrated up to TRL 6/7. This puts the technology at the pilot-to-deployment transition stage.

Does this integrate with our existing rail management systems?

Integration was a core design goal. The project used a common system architecture and Conceptual Data Model to ensure coherence across all demonstrators. The IAMS integration demonstrator specifically showed how heterogeneous inputs from various monitoring systems can be collected through a common monitoring solution.

What regulatory standards does this align with?

The project was designed to meet ISO 55000 best practice for asset management in the railway sector, as explicitly stated in the objectives. It also aligns with Shift2Rail Innovation Programme 3 standards for intelligent asset maintenance.

What ongoing support or training would be available?

Based on available project data, the consortium includes 4 universities and 3 research organizations alongside 19 industry partners. The project produced 34 deliverables including assessment reports on benefits and impact. Post-project support would need to be arranged with individual consortium members, particularly the coordinator Hitachi Rail STS.

Consortium

Who built it

This is one of the most industry-heavy rail research consortia you'll find: 19 out of 28 partners are from industry (68%), led by Hitachi Rail STS — a global player in rail signalling and technology. The consortium spans 10 countries across Europe, bringing together operators, technology suppliers, and infrastructure managers alongside 4 universities and 3 research centres. With only 3 SMEs, this is primarily an enterprise-grade effort. The strong industry presence and a major commercial coordinator (Hitachi) significantly increase the likelihood that results will move toward market deployment rather than staying in academic papers.

How to reach the team

Hitachi Rail STS SPA (Italy) — reach out to their innovation or business development team for licensing and deployment discussions

Order a report on this consortiumSee HITACHI RAIL STS SPA profile →
Next steps

Talk to the team behind this work.

Want an introduction to the IN2SMART2 consortium? SciTransfer can connect you with the right technology partner for your specific rail maintenance challenge.

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