IN³ Season IV · Ingérop España

From blind spotsto data points

Non-intrusive predictive IoT monitoring system
for legacy railway fleets.

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The challenge

Legacy rolling stock
has no voice

Millions of vehicles run without any condition monitoring system. The result: unexpected failures, delays, and avoidable maintenance costs.

0%

of the European short/medium-distance railway fleet is between 15 and 30 years old with no integrated TCMS

0

Doors are the leading cause of operational incidents in metro and commuter rail, above bogies and traction

0×

Corrective maintenance is 10× more expensive than predictive — and avoidable with continuous monitoring

The solution

Monitoring
without intervention

IN-SIGHT installs in a few hours, without modifying existing software or vehicle wiring. Four steps from unknown to full control.

Architecture

Three layers,
one continuous flow

From the sensor on the bogie to the alert on the dashboard — in under 30 seconds.

Raspberry CM4 MEMS MFXSTR Azure IoT Hub Azure Data Explorer Extended Kalman Filter Golden Run Protocol MQTT / TLS 1.3 Python · KQL
Resources

Technical documentation

Access the technical documents of the IN-SIGHT programme.

Technical Whitepaper

System architecture, MEMS sensors and EKF algorithms for anomaly detection in railway rolling stock.

Product Sheet

Executive summary: value proposition, use cases at TMB and Renfe Cercanías, and estimated ROI vs. corrective maintenance.

Security & Compliance

System security framework, TLS/MQTT encryption protocols and regulatory compliance for operation in critical railway environments.

Golden Run Protocol

Methodology for capturing, validating and approving the vehicle health baseline. Complete operational guide for fleet engineers.

Contact

Talk to the team

Do you have a fleet without condition monitoring? Tell us about your case and we'll arrange a technical demo at your facility.

alejandro.guerrero@ingerop.es
Season IV · 2025–2026 Innovation programme — Ingérop España

Candidate for the
XXIII Talgo Prize
for Technological Innovation

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