Global Warming Temperature Predictor

This is what the website looks like when you first open it.
This is the average temperature this year.
This is the prediction of the average temperature in 2200

Inspiration

Our desire was to educate people and predict future temperatures, helping us gain a deeper understanding of our changing environment and world.

What it does

This web app takes in one input. This input is any year. Once you enter the year, the website will give you a estimate of the average temperature of that year.

How we built it

To begin with, we found our dataset. Using Jupyter notebooks we removed columns we don't need and removed any NaN values. Next, we were given the average temperature of every month since 1743 which was a lot of entries so we got the average of every year. Once we got our dataset, we used the sklearn library to train the model. we imported our model into our app.py file and used flask to create the backend. Next we created the front end using HTML and CSS. We then linked the front end and the backend using the POST method.

Challenges we ran into

Difficulties in understanding new programming languages
Difficulty using Google cloud API
Difficulty understanding Flask
Difficulty linking the backend to the front end

Accomplishments that we're proud of

Effective networking and teambuilding at the time of event
Successful integration of our idea into software
Ability to find the proper dataset for our needs

What we learned

We learned:

Basic website development
Dataset acquisition
Creative problem solving and solution generation
Familiarized certain teammates with HTML and CSS programming

What's next for Global Warming Temperature Predictor

Our next steps are:

Add a temperature change button
- This is to see the temperature change from the present to the year you entered
Add more cities
Add a carbon footprint tracker