Inspiration
Gives an extra edge in freight capacity planning by considering realtime and disruption data from across the internet.
What it does
Creates capacity prediction models created based on historical and realtime data available
How I built it
By collecting data across different sources of relevance and then mapping it to the capacity predictions of relevance for the freight carrier.
Challenges I ran into
Choosing right APIs and collecting relevant data
Accomplishments that I'm proud of
Bringing in dynamic aspects to capacity planning to optimize the capacity and help in creating new services and market places
What I learned
Challenges and importance of capacity planning for air freight industry
What's next for OptiSales
Optimize solution further by using the realtime capacity view of the airline. Bring in feature to find out possible partnering options considering the possible routes from trucking companies and partner airlines
Built With
- apache-cxf
- bbc-news-api
- git
- google-maps
- html5
- javascript
- jquery
- lufthansa-api
- maven
- predict-hq-api
- rest
- spring
- spring-boot
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