Rail yard with digital overlays showing data tracking and operational intelligence

Deployment Path

The program uses a phased approach that allows TTX to evaluate operational value before expanding deployment. Each phase builds on the previous one.

Phase 1 Operational Demonstration, Phase 2 Facility Deployment, Phase 3 Network Expansion

Phase 1 Operational Demonstration

Duration: 90 days

A 90-day POC demonstrating drone capture workflows and automated analytics for railcar inspection and yard intelligence.

Outcome: Validated workflows for collecting inspection and yard operational data.

Phase 2 Facility Deployment

The system transitions into routine operational use at a facility. Phase 2 includes two components.

Operational service

Ongoing operation of the deployed drone capture and analytics system including:

Scheduled drone capture operations

Regular capture runs according to operational schedules.

Dock monitoring and flight oversight

Monitoring of autonomous dock operations and flight execution.

Automated data processing

Computer vision and analytics processing of captured imagery.

Operational dashboards

Operator-facing dashboards for inspection review and yard visibility.

Capability development

Expansion of system capabilities including:

Phase 2 Outcome: An operational capability supporting inspection efficiency, yard visibility, and Autonomous Yard Intelligence at the facility level.

Digital twin view of rail yard system with monitoring and asset tracking

🗺 Phase 3 Network Expansion

The system can expand beyond a single yard.

Key activities

Examples of analytics

Phase 3 Outcome: A scalable operational capability supporting multiple yards and the continued development of Autonomous Yard Intelligence across the network.

Strategic value: Inspection Automation, Yard Visibility, Network Intelligence

📊 Strategic Value Path

🔍 Stage 1 — Inspection Automation

(Phase 1 + Phase 2)

Initial deployments focus on improving the efficiency and consistency of railcar inspections through drone capture and automated analytics.

Potential benefits:

  • Improved inspection coverage
  • More consistent inspection documentation
  • Reduced manual inspection time
  • Digital inspection records

Outcome: An Autonomous Yard Intelligence capability that continuously collects railcar condition, location, and operational data.

📍 Stage 2 — Yard Operational Visibility

(Phase 2 expansion)

Once drone data is regularly captured, the same system can provide improved visibility into railcar positions and yard activity.

Potential capabilities:

  • Drone-based yard scans
  • Automated railcar identification
  • Track-level car location mapping
  • Yard activity visualization

Outcome: A continuously updated digital view of yard activity.

📊 Stage 3 — Network Asset Intelligence

(Phase 3)

As inspection data accumulates across facilities, analytics can begin to provide insight into railcar condition trends across the fleet.

Potential capabilities:

  • Fleet-level defect analytics
  • Trend detection across inspections
  • Maintenance planning insights
  • Early indicators of emerging issues

Outcome: A data-driven view of railcar condition across the network.

Long-Term Vision

Over time, drone capture and analytics can support:

The system assists inspectors and yard operations rather than replacing them. Each phase builds on the previous one, allowing TTX to evaluate operational value before expanding deployment.