Predictive Fleet Analytics Platform
Built a real-time analytics and forecasting platform reducing fleet downtime by 27%.
Case Study
Project Overview
A logistics provider needed visibility into fleet health before breakdowns caused costly delays. We built a real-time telemetry and machine-learning platform that predicts maintenance needs before failures occur.
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ClientLogistics & Freight Provider
IndustryLogistics
CategoryData & AI
Duration7 months
The Challenge
- Reactive maintenance causing costly unplanned downtime
- Disparate telemetry data across vehicle makes and models
- No unified dashboard for fleet health
- Need for accurate maintenance forecasting
Our Solution
- Real-time telemetry ingestion pipeline from IoT sensors
- Predictive maintenance models trained on historical failure data
- Unified fleet health dashboard with alerting
- Automated maintenance scheduling recommendations
Technology
Tech Stack Used
Python
Apache Spark
Azure ML
Power BI
IoT Hub
Impact
Results That Matter
0%
Reduction in Fleet Downtime
0%
Lower Maintenance Costs
0+
Vehicles Monitored
0%
Prediction Accuracy
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