GreenX

Inspiration

We love traveling, and the idea of being able to guide customers with AI in a more responsible and sustainable way!

What it does

GreenX uses a prompt to suggest different HotelPlan destinations to customers, taking into account preferences and sustainability!

How we built it

First, we came up with a set of criteria on which a hotel could be judged using its details provided in HotelPlan's data. Then we used the OpenAi library in python to determine the users sentiment towards each of the criteria. We combined the knowledge of the hotels' strengths and the users preferences along with statistics we derived regarding the possible sustainability of the hotel and the location to rank the hotels.

Challenges we ran into

At first, we were totally committed to the Siemens challenge, but after changing our minds a dozen times because we hadn't found a way of processing the rail data that suited us, we decided to move on... so we switched from trains to travel because we had some idea! No wonder we ended up doing AI like three quarters of the challenges this year...

Accomplishments that we're proud of

Our algorithm for matching makes use of modern techniques for interpreting text from a user and sorts a large number of hotels on good number of criteria quickly. We are also very proud of the things we learned.

What we learned

We learned about using the OpenAi/GMaps API, how to deal with big JSON files and for the majority of the team try to understand German/French data ;)

What's next for GreenX

Improve understanding of the prompt, increase the number of parameters for better matching and develop a better algorithm to determine trip sustainability.

Built With

• google-maps
• openai-api
• python