Yard Carbon Footprint Intelligence
What we deliver
The Problem (Before)
Facilities have no visibility into yard-level carbon emissions: spotter fuel, gate idle time, reefer energy, empty repositioning. ESG reporting is shipment-level only.
Yard Coordinator, Facility Manager, Sustainability Analyst
The Outcome (After)
DY tracks spotter moves, idle time, and reefer energy usage. Combined with gate throughput data and trailer repositioning frequency, FourKites calculates facility-level carbon footprint and benchmarks against network norms.
FourKites measures carbon at the yard level — spotter fuel, gate idle, reefer energy, and empty repositioning — turning shipment-only ESG reporting into facility-level Scope 1 and 2 visibility.
How it works
The system tracks spotter moves, idle time, reefer energy, and empty repositioning to calculate facility-level carbon footprint and benchmark it against the network.
- Spotter efficiency benchmark (moves per unit) by facility type
- Gate/yard idle-time norms by facility throughput volume
- FourKites network by facility type, size, and industry
- Reefer energy fuel consumption patterns by dwell duration
This intelligence exists because the Graph aggregates behavior across 882 enterprise shippers, 10,164 carriers, and 3.6 million facilities over 11 years. No single company's data could produce it.
The intelligence layer is what creates the gap. Building the basic capability is straightforward. Building it on top of 11 years of cross-company facility and yard intelligence is what cannot be replicated with software alone.
Yard Twin, Shipment Twin
Cross-company facility and yard intelligence powering every decision
FourSight AI: "What is our yard carbon footprint by site this month?"
Custom Insights:
- Facility carbon footprint dashboard (spotter fuel, idle time, reefer energy)
- Emissions benchmarking against network norms
Yard Intelligence and Optimization
- Multi-Site Yard Intelligence and Predictive Capacity Planning
- Revenue-Aware Yard Prioritization
- Demand-Driven Yard Planning
- Predictive Facility Capacity Planning
- Autonomous Yard Decisioning
Validation
Deployment Evidence
Expected Impact Range
Related outcomes
Every trailer in the yard: located, identified, and tracked in real time.
Gate staffing eliminated. 100% automated check-in and check-out using computer vision.
Spotter tasks dispatched and optimized automatically. No radio, no whiteboard, no guesswork.
One billion hours of operational work completed by AI agents over the next decade.
