Logistics & Supply Chain
Real-Time Fleet Route Optimization
KafkaSpark StreamingRedisPython
The Challenge
A national freight carrier operated 2,400+ vehicles with routes planned the night before using static spreadsheets. Fuel costs were climbing, on-time delivery sat at 74%, and drivers had no visibility into live traffic or weather disruptions.
The Approach
Ingested GPS telemetry, weather APIs, and traffic feeds into a streaming pipeline processing 8M events per hour. A dynamic routing engine re-optimized routes every 15 minutes, pushing updated turn-by-turn instructions directly to driver tablets.
The Impact
18% reduction in fuel consumption
On-time delivery improved from 74% to 93%
8M telemetry events processed per hour
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