Real-Time Fleet Routing Architecture
Intelligent telemetry and route optimization at fleet scale
A persistent telemetry tracking and geospatial calculation system built to handle high-frequency IoT location ingest across 5,000+ vehicles.
A persistent telemetry tracking and geospatial calculation system built to handle high-frequency IoT location ingest across 5,000+ vehicles.
Project Overview
We engineered a real-time fleet management platform for a national logistics provider operating 5,000+ vehicles. The system ingests GPS telemetry from IoT devices at 1-second intervals, processes geospatial calculations for route optimization, and provides real-time visibility to dispatchers and customers. ML-powered route optimization reduced fuel consumption by 25% while improving on-time delivery rates from 78% to 94%.
The Challenge
The logistics provider relied on manual dispatch processes with whiteboard tracking. Dispatchers had no real-time visibility into fleet locations, route deviations went undetected for hours, and customers received inaccurate delivery ETAs. Fuel costs were spiraling due to inefficient routing, and driver utilization was below 60%.
Our Solution
We deployed IoT telemetry devices across the fleet with cellular and satellite backup connectivity. A time-series database (TimescaleDB) ingests 5,000+ GPS coordinates per second with automatic downsampling for historical analysis. A reinforcement learning model provides dynamic route optimization accounting for traffic, weather, delivery windows, and driver hours-of-service regulations.
Business Impact
Fuel costs dropped 25% through optimized routing. On-time delivery improved from 78% to 94%. Real-time tracking eliminated manual check-in calls, saving 40 dispatcher hours per week. Customer satisfaction scores improved 35% with accurate ETAs and proactive delay notifications.
Visual Highlights
Key Features
Technical capabilities that made this project successful
IoT Telemetry Pipeline
High-frequency GPS ingestion from 5,000+ vehicles with 1-second polling intervals and satellite backup.
RL Route Optimization
Reinforcement learning model optimizing routes for fuel efficiency, delivery windows, and driver HOS.
Real-Time Geofencing
Automated zone detection with arrival/departure events, route deviation alerts, and ETA recalculation.
Predictive ETA Engine
ML model incorporating traffic patterns, weather data, and historical performance for accurate delivery ETAs.
Customer Tracking Portal
White-label customer portal with real-time vehicle tracking, delivery status, and proactive notifications.
Dispatch Command Center
Unified dashboard with live fleet map, workload balancing, and automated dispatch suggestions.
Technology Stack
Modern toolchain selected for this specific use case
IoT & Hardware
- GPS/GLONASS
- LTE-M
- LoRaWAN
- MQTT
- AWS IoT Core
Data & ML
- TimescaleDB
- PostgreSQL
- Apache Kafka
- Python
- PyTorch
Geospatial
- Mapbox GL
- Turf.js
- PostGIS
- H3
- OSRM
Frontend
- React
- Next.js
- Mapbox
- Tailwind CSS
- WebSockets
Project Timeline
Delivered in phased increments with continuous stakeholder validation
IoT Deployment
Telemetry hardware installation across fleet, connectivity testing, and baseline data collection.
Data Pipeline
Time-series ingestion pipeline, geospatial processing, and real-time event stream architecture.
ML Route Optimization
Reinforcement learning model training on 6 months of historical route data with iterative validation.
Platform Launch
Dispatch dashboard, customer portal, and mobile app rollout with fleet-wide training and cutover.
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