Movynn

Inspiration

Traditional logistics systems are inefficient, with manual processes and high fuel costs. We aimed to build a smarter, data-driven solution.

What it does

Movynn optimizes logistics by recommending the best vehicle, predicting fuel usage, and providing route visualization using maps.

How we built it

Built using React (frontend), Spring Boot (backend), MySQL (database), and Python ML models, integrated with Google Maps API.

Challenges we ran into

Integrating ML with backend systems and handling real-time data efficiently was challenging.

Accomplishments

Successfully combined ML with full-stack development to create an intelligent logistics platform.

What we learned

Gained experience in full-stack development, ML integration, and system design.

What's next

Add GPS tracking, traffic-based routing, and a mobile app.

Built With

• java
• maven
• springboot