Logistics Architecture Case Study
Client: TransPacific Freight Duration: 5 Months

Autonomous Real-Time Fleet Tracking & AI Route Optimizer

Centralizing 12,000+ freight vehicles into a geospatial dispatch engine saving 1.2M gallons of fuel.

Autonomous Real-Time Fleet Tracking & AI Route Optimizer

Key Business & Engineering Outcomes

1.2M Gal
Fuel Saved

Yearly reduction in fuel consumption across all routes

< 800ms
Telemetry Latency

Live location updates streamed to customer tracking portals

98.7%
On-Time Delivery

Improved delivery accuracy from previous baseline of 84%

3.5x
Dispatch Capacity

Operations team can manage triple the fleet size with same headcount

The Business & Technical Challenge

Legacy GPS tracking suffered 4-minute telemetry lags, leading to blind spots, excessive driver idle times, and dispatch inefficiencies costing millions annually.

The Entecra Architectural Solution

We engineered an edge-to-cloud IoT ingestion gateway using MQTT brokers, ClickHouse spatial time-series databases, and custom AI genetic algorithms for real-time dispatching.

Architecture Blueprint & Implementation Phases

1

High-Throughput IoT Ingestion

Engineered an MQTT ingestion pipeline handling 85,000 telemetry pings per second with sub-second stream persistence.

2

Geospatial Time-Series Storage

Deployed ClickHouse cluster for ultra-fast spatial queries and 100x data compression over historical GPS trails.

3

Predictive Dispatch Neural Network

Trained route optimization models dynamically adjusting stops based on real-time traffic and port unloading queues.

Our dispatchers have total visibility into our global fleet. Entecra transformed our operations from reactive firefighting to predictive mastery.

David Sterling
Director of Global Operations, TransPacific Logistics

Architecture & Tech Stack

ClickHouseGoMQTTKubernetesPythonReactGoogle Maps Platform
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