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Case · edge AI · 2025—2026

Inspection of oil and gas infrastructure

Data processing
a week → 1 hour
the report is ready at base

Task: inspect routes and facilities from a helicopter without processing terabytes of video by hand after the flight.

The flight, and the chip on board the helicopter follows the pipeline; what enters the camera’s footprint is detected on the Jetson there and then, and the report exists before it lands
AI NVIDIA Jetson edge AI on board — detection is computed here, with no internet
Detections in flight · no internet, no cloud back at base · the report is ready
  • Equipment — a valve stationGroundingDINO / SAMframes1 event
  • VehicleYOLOframes1 event
  • PersonYOLOframes1 event
  • Anomaly — a spill by the pipeSAMframes1 event

4 events · 0 operators on board

How it works

A YOLO cascade for people and vehicles, GroundingDINO / SAM for equipment and anomalies. Offline mode with local weights, tracking with event deduplication.

Results

a week → 1 h
to process the data
3 → 1
people in the process
0
operators on board

The report exists on landing

It is produced during the flight rather than a week after it

Inspection without an operator

Vision on the chip runs the survey itself, and the crew shrank from three to one

Stack

NVIDIA Jetson (L4T) · PyTorch · ONNX · YOLO · GroundingDINO · SAM

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