Context
Citywide traffic analytics ran purely in cloud GPUs with high storage costs. The agency needed to expand coverage without expanding budget.
Approach
- •Edge batching on Jetson; Triton/DeepStream pipelines
- •Hybrid edge↔cloud sync; cold-tier storage
- •Model schedule + accuracy monitoring; canary rollouts
Results
Methodology →Cloud GPU hours/year
4,800 → 2,976
-38%
Storage footprint
180 TB → 117 TB
-35%
Infra spend YoY
-29%
Cost reduction
Detection accuracy
±1.5 pp
Maintained
Stack & Integrations
Jetson
DeepStream
Triton
S3/Glacier
ArcGIS
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