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10 Leo Ave, Tarneit VIC 3029, Australia

Office #51 3rd Floor Crystal Arcade, LMQ Road, Multan

1910 Pacific Ave Suite 2000
PMB2461, Dallas, Texas 75201

+61 421 702 706

connect@devvibe.com

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Autonomous Fleet Management System

Autonomous Fleet Management System

We built a connected fleet management solution that puts every vehicle on the map and tracks them in real time. By combining IoT devices inside trucks and buses with a powerful web application, operators can see where their fleet is, how it’s performing, and when it needs attention. The result is fewer surprises, lower costs, and more control over daily operations.

  • Real-time vehicle tracking with live Google Maps integration
  • IoT-enabled monitoring of speed, idle time, and movement status
  • Predictive maintenance alerts to prevent costly breakdowns
  • Interactive dashboards turning fleet data into actionable insights

Technologies and Tools:

IoT Firmware (C/C++)
Node.js
Express.js
React
MongoDB
Google Maps API
WebSockets
Arduino
Raspberry Pi
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Process

Our solution embedded IoT devices directly into each vehicle to stream live data into a centralized web dashboard. Operators could monitor every movement on Google Maps, track speed and idle time, and instantly know when a vehicle was in motion or at rest. Beyond location tracking, the system analyzed performance data to highlight vehicles needing maintenance before costly issues occurred. 

Graphs and insights transformed raw data into clear actions, helping operators manage fleets with confidence. The challenge was clear: fleet operators had little real-time visibility into their vehicles and often relied on manual reporting, which meant delays, inefficiencies, and unexpected breakdowns.

Artificial Intelligence refers to the development of computer systems that can perform tasks that would typically require human intelligence. It involves the creation of algorithms and models that enable machines to learn, reason, perceive.

Adam Peterson
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Fleet Managment
Fleet Managment
Fleet Managment
Fleet Managment

Key Outcomes

The system gave businesses real-time visibility that reduced downtime and improved accountability across their fleets. Predictive maintenance lowered repair costs, route optimization saved fuel, and faster insights meant operators could respond to issues before they turned into problems.

  • Lowered operational risks with proactive monitoring
  • Data-driven decisions replacing manual guesswork
  • Stronger oversight with every vehicle accounted for in real time
  • Greater transparency between management, drivers, and clients
accuracy achieved in monitoring
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faster response time to incidents
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vehicle tracks monthly
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