WingIt

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  Intelligent Seating Results

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  Panel for Demo Input

Inspiration

This came from our desire to meet fun new people on our Delta Flights!

What it does

This web application allows a user to connect their Facebook or LinkedIn accounts instead of manually selecting a seat and determines an intelligent seating arrangement based off of unique Facebook likes, or industry worked in. In addition, it analyzes a user's tweets to curate a movie recommendation based off of mood and the user's Facebook likes.

How I built it

The backend stack consists of Django and PostgresSQL. The app interacts with Facebook Graph API to get information about a user's likes and the count of likes for a given page, Twitter API to get a user's tweets for future semantic analysis, Microsoft Azure Cognitive Services to analyze the user's tweets to determine mood, and a database of existing in-flight movies. The basic HTML template comes from Templated.co and was customized extensively.

Challenges I ran into

Facebook requires an approval process before we could generally allow anyone to connect their account to our project. To show our project in action with this hurdle, we created a demo panel to customize likes. LinkedIn API presented some challenges in properly authenticating users through their OAuth method. The error messages were quite ambiguous.

What's next for WingIt

Interacting with an existing flight seating API to see which seats are available on a flight. Using Twilio API to send out a text to users mentioning the most impactful mutual like between two people sitting next to each other.

Built With

• azure
• css
• django
• facebook-graph
• html
• javascript
• python
• twitter