Autonomous Yard Intelligence Pilot
Wanda Analytics will use drone automation and AI-assisted analysis to evaluate yard visibility, inventory awareness, inspection workflows, and operational intelligence for TTX.
Pilot Goals
Automated yard inventory
Systematic capture and indexing of yard assets to build a current, searchable inventory.
Railcar identification and classification
OCR and computer vision to read car numbers and classify car types from drone imagery.
Yard mapping and car location visibility
Track-level mapping to show where cars sit and support switching decisions.
Inspection analytics
AI-assisted inspection workflows to flag defects and safety appliances.
Mission Types
Five mission types support the pilot. Types 1 and 2 are Phase 1 core. Type 3 is optional in this pilot. Types 4 and 5 are suggested for later phases as capabilities mature.
Mission Type 1 — Yard Survey Mission
Phase 1Broad coverage of the yard to capture inventory and build the operational map. Sets the baseline for car counts and layout.
Mission Type 2 — Close Inspection Mission (Rail Car)
Phase 1Targeted close-up inspection of rail cars for defect detection and safety appliance checks.
Mission Type 3 — Close Inspection Mission (Material Inventory)
Optional in this pilotFocused capture of material and equipment inventory for cycle counts and layout optimization.
Mission Type 4 — On-Demand Spot Inspection (Blue Flag / Brake Engaged)
Suggested Phase 2Quick verification of blue signal and hand-brake status when requested for work-zone safety.
Mission Type 5 — Close Inspection Mission (Switch Position Verification)
Suggested Phase 3Verification of switch positions to support switching logic and yard operations.
Daily Operational Concept
How drones run in the yard day-to-day:
OCR-style patrol to capture yard state and update the map.
Routine inspection runs to identify defects and safety issues.
Spot verifications (e.g., blue flag, brake engaged) when requested.
Additional close inspections or mapping as needed.
90-Day Pilot Timeline
Work runs in parallel over 12 weeks. Tasks grouped by phase: Setup → Build → Integrate. Click a task for details.
Deliverables
What TTX can expect from the pilot:
- Structured drone data collection workflows — Repeatable capture and ingestion routines.
- Initial yard map / operational interface — Track-level view of the yard.
- OCR and classification outputs — Railcar numbers and car types from imagery.
- Inspection analytics prototypes — AI-assisted defect and safety-appliance checks.
- Findings visualization and roadmap — Summary and next-phase deployment recommendations.
TTX Use Case Difficulty vs Value
Operational use cases mapped by implementation difficulty and suggested phasing. Phase 1 builds foundational capabilities; Phase 3 targets advanced operations.
| Use Case | Difficulty | Why | Phase |
|---|---|---|---|
| Material audits / cycle counts | Easy | Requires OCR + car location | Phase 1 |
| Yard mapping | Easy | Mostly photogrammetry / manual mapping | Phase 1 |
| Track inspections | Easy | Simple visual imagery review | Phase 1 |
| Lost railcar search | Easy | OCR + yard map | Phase 1 |
| Layout optimization | Easy | Analysis of mapped yard data | Phase 2 |
| Yard audits | Medium | Requires consistent car location accuracy | Phase 2 |
| Box car inspection | Medium | Object detection models | Phase 2 |
| Auto rack inspection | Medium | Tall structure but visually consistent | Phase 2 |
| Tall car inspection | Medium | Requires different capture geometry | Phase 2 |
| Blue signal verification | Medium | Object detection but clear visual signal | Phase 3 |
| Hand brake verification | Medium | Requires better resolution + angles | Phase 3 |
| Auto rack bellows inspection | Hard | Flexible structure + lighting variation | Phase 3 |
| Switch position tracking | Hard | Small objects + occlusion | Phase 3 |
| Switching optimization | Hard | Requires movement tracking + operations logic | Phase 3 |
| Yard movement planner | Hard | Needs historical movement + predictive logic | Phase 3 |