FleetOps — Fleet Management & Route Optimization
An IoT-powered fleet management system with real-time GPS tracking, AI-driven route optimization, and predictive maintenance alerts for logistics companies.
Project Overview
FleetOps is a fleet management and logistics optimization platform built for a national distribution company operating 1,200+ vehicles across 6 regional hubs. The system provides real-time GPS tracking, AI-powered route optimization that accounts for traffic, weather, and delivery windows, and predictive maintenance alerts based on IoT sensor data from each vehicle. The Python backend processes telemetry from thousands of sensors, while the React dashboard gives dispatchers a live operational view with drag-and-drop route adjustments.
Timeline
14 Weeks
Team Size
6 Engineers
Platform
React + Python
Industry
Logistics
Key Results
1,200+
Vehicles Tracked
31%
Fuel Savings
99.2%
On-Time Delivery
45%
Less Downtime
Dispatchers planned routes manually using static maps and driver experience. There was no visibility into vehicle location between checkpoints, and unplanned breakdowns caused an average of 340 hours of downtime per month.
Manual route planning added an average of 23% extra mileage per trip
No real-time visibility — dispatchers relied on driver phone calls for updates
Unplanned vehicle breakdowns causing 340+ hours of monthly fleet downtime
Fuel costs rising 12% year-over-year with no optimization strategy
We deployed IoT OBD-II devices across the fleet and built an AI routing engine that learns from historical delivery patterns. The predictive maintenance model analyzes engine telemetry to flag issues 2-3 weeks before failure.
Deployed OBD-II IoT devices across 1,200 vehicles streaming telemetry every 10 seconds
Built an AI route optimizer using historical data, live traffic, and delivery time windows
Trained a predictive maintenance model that detects anomalies 2-3 weeks before failure
Created a dispatcher dashboard with live map, drag-and-drop rerouting, and driver messaging
FleetOps reduced total fleet fuel consumption by 31% and cut unplanned downtime by 45%. On-time delivery rates improved from 84% to 99.2%, and the platform paid for itself within 4 months through fuel savings alone.
Fuel costs reduced by 31%, saving $2.8M annually across the fleet
Unplanned downtime decreased by 45% through predictive maintenance
On-time delivery rate improved from 84% to 99.2%
Route optimization reduced average daily mileage per vehicle by 19%
Technologies Used
“FleetOps paid for itself in four months just on fuel savings. But the real win is predictive maintenance — we catch problems weeks before they strand a driver. Our fleet has never run this efficiently.”
Sameer Khan
Director of Logistics, SwiftHaul Distribution
