FlyFair

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Graph we created to get an emissions heuristic

Inspiration

QRT's meet in the middle challenge at Durhack 2025 inspired us to think of how we can calculate greener ways to travel.

What it does

This a web tool that given the 13 QRT offices and the number of people travelling from each office, it calculates an optimal meeting location to reduce carbon emissions.

How we built it

One person worked on front end, one on back end helpers for processing flight data, one working on the algorithm, and the final person working on project design and gathering auxillary data. We used python for the backend processing using the Polars package and hosted the web server using Flask in python.

Challenges we ran into

We wanted to calculate the costs of each flight but APIs that get live flight prices costed money that we weren't willing to spend for a hackathon project and we couldn't find historical flight price datasets. Likewise, finding a global train time dataset also proved very difficult which is unfortunate as we also wanted to find ways to factor train travel in to the calculation.

Accomplishments that we're proud of

We're proud of the product we've made give that we on had 24hrs to create it. It would not have been possible to do this without good team work and effective distribution of responsibilities.

What we learned

We've learned a lot about carbon emissions in the aviation industry and the cost of flying compared to other modes of transport. We've also learned about how challenging of a task route planning is, especially when there are multiple factors that have to be balanced.