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Transportation & Rail

31% fewer track incidents, 40% faster ROW clearance, and thermal failures caught before service disruption. No wayside system replacement.

Rail and transportation AI from Allerin is right-of-way monitoring, track defect detection, rolling stock thermal monitoring and signal and switch verification on wayside and depot cameras, measured by incidents, clearance time and failures caught before service.

Who is this for?

Infrastructure directors, safety managers and rolling stock operations teams at Class I, regional and commuter railroads, and the DOT and MPO traffic data managers who run SENTRA on the road side. It works with the wayside systems you already have rather than replacing them.

What problem does it solve?

Track-caused incidents rarely come from an unknown defect. They come from a known class of defect that sat low on a list too long to walk. Vegetation encroachment is the same: a corridor survey that takes weeks per subdivision produces a violation list that is out of date before the work orders are written.

In the depot, a hot bearing or a dragging brake gives a thermal signature days before it fails, and in the field a signal aspect or a switch position can be wrong for longer than anyone would like to admit. The data exists. The problem is that it lives in cameras and arrays nobody has time to watch.

How does it work?

RailGuard detects vegetation encroachment and clearance violations (structure gauge, overhead) from corridor imagery, maps each with GPS, scores severity and generates the work order. TrackSentinel classifies cracks, wear and ballast fouling from geometry car or inspection vehicle imagery, prioritizes by severity and traffic volume, and exports inspection logs aligned with FRA Part 213, with GPS, timestamps and inspector override on every record.

FleetTherm reads depot-mounted thermal arrays for wheel, bearing and brake anomalies, with component-level tracking and a lead-time estimate so the intervention can be scheduled, not forced. SignalEye verifies signal aspects and switch positions from wayside cameras and raises faults through the PTC integration.

Accuracy is stated, not implied. FleetTherm runs at 92 to 96 percent on bearing and wheel thermal anomalies, every alert carries the thermal image, and the false-positive rate is tunable by the maintenance team. RailGuard is trained on leaf-on and leaf-off imagery, with seasonal baselines set in the proof of concept and drift checked quarterly.

Quick wins

  • Right-of-way monitoring & clearance (RailGuard)
  • Track defect detection (TrackSentinel)
  • Rolling stock thermal monitoring (FleetTherm)
  • Signal & switch monitoring (SignalEye)

Capabilities

  • Computer Vision
  • Predictive Maintenance
  • Safety Analytics

Solutions for Transportation & Rail

What does it connect to?

  • CMMS and EAM: Maximo, SAP PM, Infor EAM
  • GIS: Esri ArcGIS and linear referencing (LRS)
  • PTC: Wabtec, Alstom and Siemens fault reporting APIs
  • Existing wayside detection (Salient, Lynxrail and others) through Modbus, OPC-UA and REST

How is it deployed, and how long does it take?

Wayside cameras (visible and thermal) with Jetson or x86 edge compute, depot-mounted thermal arrays, and a cloud or on-prem analytics tier. Class I railroads run fully on-prem with no cloud dependency, Class II and III carriers usually take the cloud option, and hybrid edge-plus-cloud covers the rest.

These systems add to your HBD and WID detectors; they do not replace them, and we would not recommend that anyone try.

Proof of concept in 2 to 4 weeks, pilot in 6 to 8, full deployment in 60 to 90 days. First value: 4 to 6 weeks for right-of-way monitoring, 6 to 8 weeks for track defects.

Related products and services

  • SENTRA

    Edge CV for wayside cameras and depot thermal imaging; low-latency inference for real-time alerts

  • Data & Analytics Platform

    CMMS integration (Maximo, SAP PM), GIS mapping, FRA reporting

Proven ROI

31% fewer track incidents
Regional freight railroad reduced track-caused derailments from 13 to 9 annually using TrackSentinel for defect prioritization
40% faster ROW clearance
Commuter rail system cleared 160 vegetation violations in 45 days (vs. 75 days historical) with RailGuard automated work orders

Frequently asked questions

Yes. TrackSentinel generates inspection logs aligned with FRA Part 213 (track safety standards). All defect records include GPS, timestamps, severity classification, and inspector override capabilities.
Absolutely. We integrate with Salient, Lynxrail, and other wayside systems via standard protocols (Modbus, OPC-UA, REST APIs). RailGuard and TrackSentinel augment, not replace, existing HBD/WID systems.
FleetTherm achieves 92-96% accuracy on bearing/wheel thermal anomalies. False positive rates are tunable; all alerts include thermal imagery for maintenance team verification.
SignalEye integrates with Wabtec, Alstom, and Siemens PTC systems via fault reporting APIs. Signal aspect and switch position data can trigger automated PTC alerts or work orders.
Yes. Full on-prem deployment is supported for Class I railroads. All processing and storage remain within your infrastructure with no cloud dependency.
For ROW monitoring: 4-6 weeks (baseline scans, first violation report). For track defects: 6-8 weeks (PoC with historical imagery, first prioritized work order queue).
RailGuard is trained on multi-season imagery (leaf-on/leaf-off). Seasonal baselines are established during PoC, and model drift is monitored quarterly with retraining triggers.

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