From Rolling Stock Data to Operational Decisions: Trilogical at InnoTrans 2026

Trilogical showcased its Control FREAK and RailBlazer platforms at InnoTrans 2026 in Berlin, emphasizing the transition from raw rolling‑stock data to actionable information for operations, maintenance and engineering teams. The company highlighted how real‑time and historical sensor data from locomotives, multiple units and freight wagons can be combined with analytical tools to identify equipment needing attention, investigate failures and improve fleet availability. For operations crews, the platform can flag issues during a live trip and provide the data required to decide on the appropriate response. Maintenance teams can use asset‑health information to prioritise work and move toward proactive maintenance, while engineering staff can analyse failures against historical sensor data, compare recurring events and test analytical conditions before applying them fleet‑wide.

RailBlazer extends telematics and condition monitoring to unpowered freight cars, integrating location, movement, load monitoring, weight estimation, impact measurements and handbrake status. This enables operators to assess whether a group of cars is loaded and ready for departure, requires attention or has recorded a condition that warrants inspection. Other demonstrations included wheel‑flat detection, track‑level positioning and asset‑utilisation analysis, all aimed at reducing dwell time, improving utilisation and providing maintenance teams with earlier, more precise condition data. RailBlazer is designed for a ten‑minute physical installation with no major car modifications and a battery life of approximately six years, depending on configuration.

For environments with limited cellular coverage, Trilogical’s Intra‑Train Mesh connectivity allows information to be transferred between cars and the locomotive, ensuring critical safety events reach the locomotive without relying solely on individual car cellular links. The platform presents tailored information to each stakeholder while maintaining a common data environment, enabling knowledge reuse across powered and unpowered stock. AI is applied selectively, with rule‑based or statistical methods preferred when operating conditions are well defined, and AI reserved for large volumes of historical data where pattern detection is required. The InnoTrans event also served as a forum for Trilogical to engage operators, fleet owners, OEMs and technology partners worldwide, reinforcing partnerships with Israel Railways and the State Railway of Thailand and underscoring the industry’s shift from mere connectivity to actionable, operationally relevant information.