Rail Power
A deployable platform for rail infrastructure analytics: low‑power sensing + AI models + dashboards/APIs — designed for predictive maintenance on live rail and tram networks.
System overview
Rail‑mounted nodes
Rugged, low‑power devices capture information‑rich vibration signatures while assets remain in service.
Signal intelligence
Change detection and forecasting models identify anomalies early and track progression over time.
Dashboards + APIs
Actionable insight integrates into maintenance planning, incident response and digital‑twin workflows.
Use cases
Designed to support both planned works and disruption response.
- Condition monitoring for rail defects and infrastructure degradation
- Predictive maintenance planning to avoid failures and line closures
- Corridor‑level resilience services to reduce passenger disruption
- Scenario libraries and synthetic data for rare failures (optional)
Impact measurement
KPIs should be defined per corridor using baselines (fault logs, delay attribution, maintenance records). Indicative targets can include:
- 10–20% fewer unscheduled maintenance events on relevant assets
- 15–20% fewer disruption minutes linked to infrastructure issues
- Improved detection‑to‑response time for emerging faults
Solutions blocks
This mirrors the “Solutions” section in the reference page, but tailored to Rail Power.
Predictive maintenance
Forecast degradation progression to move from time‑based to condition‑based interventions.
Failure mechanism insight
Explainable analytics to distinguish likely fault types and reduce investigative time.
Resilience services
Corridor‑level monitoring to support disruption response and multimodal passenger service continuity.