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Transportation & logistics
Real-time fleet tracking and route optimization module.
A real-time IoT tracking module that integrates with any GPS hardware to automate fleet management, saving 15% on fuel and cutting dispatcher workload by half through AI-driven routing.
15%fuel savings
100%real-time transparency
50%reduced dispatcher workload
- Industry
- Transportation & logistics
For logistics companies, visibility is the key to efficiency. We developed a specialized tracking and optimization module designed to integrate seamlessly with existing TMS platforms. By combining live IoT data with advanced geofencing and AI-driven routing, we provided the client with a command-center view of their entire fleet, turning raw GPS coordinates into actionable business intelligence.
What we were up against
- Fragmentation of data. Consolidating disparate data streams from multiple GPS hardware providers and IoT sensors into a single interface.
- Legacy system integration. Developing a standalone module that functions perfectly within an existing, inflexible infrastructure without downtime.
- Latency in real-time tracking. Ensuring that vehicle positions and status updates are reflected on the map with sub-second delay.
- Complex route recalculation. Implementing logic that triggers immediate route adjustments when a vehicle deviates or traffic conditions change.
How we solved it
- Hardware-agnostic IoT gateway. Built a robust integration layer capable of processing data from any telematics provider via MQTT and WebSockets.
- Dynamic geofencing engine. Developed a high-performance module that automatically triggers alerts for arrivals, departures or unauthorized route deviations.
- Live map visualization. Implemented a custom map layer using vector tiles to smoothly render thousands of moving assets and their historical breadcrumb trails.
- Event-driven alerts. Created an automated notification system that informs dispatchers and customers of ETAs, delays and temperature fluctuations for sensitive cargo.
Measurable impact
- 15% fuel savings. Achieved through the optimization engine, which re-routes drivers away from traffic jams and reduces unnecessary idling.
- Full fleet visibility. Achieved 100% real-time transparency across the entire supply chain.
- 50% reduced dispatcher workload. Automation of routine tracking and ETA updates allowed dispatchers to manage twice the number of vehicles.
- Improved customer satisfaction. Automated, accurate ETA updates reduced "where is my order" inquiries by 40%, significantly cutting support costs.
What we used
- AWS
- Web Development
- AI
- Real-Time
- Logistics
- Vector Database
- Python
- Django
- Next.js
- TypeScript
- PostgreSQL
- RAG AI Models
- IoT
- Redis
- Apache
- ML