1st Proposal of our Final Product (Figma screenshot)
Our MVP prototype coded in Python using Dash
Building city groups
Transparency Score brainstorming session !
Design Thinking of our Solution
Brainstorming Session of how to tackle the issue
Our Work Flow to define our problematic
Draft of a publication of our city competition result
iOS Notification Visual 2 (this would come in the iOS notification board for quick info on your city's rank)
iOS Notification Visual (this would come in the iOS notification board for quick info on your city)
iOS Notification Visual 3 (this would come in the iOS notification board for quick info on your city's energy mix)
Our lovely logo :-)
ADDRESSING CLIMATE CHANGE BEGINS IN THE CITIES
Cities are the center of everything from communication to culture to commerce. They have all the actors possible to set an agenda for a sustainable future.
However, they also are at the forefront of global climate change. Some are facing floods, others increasing sea level.
We therefore need to help citizens be aware about the stake of their city if nothing is done.
Decision makers from cities have closer relationships with how the city is doing, they can take fast decisions and implement policies quickly.
Our project uses data sets in order to classify cities within categories, in order to compare cities in a positive competition, putting forward those performing well in reducing CO2 emissions. Thus, this encourages the others to do the same.
We want to encourage people to reduce CO2 emissions. While we must admit most of us are more and more incentivised against words, visuals still stick to our minds. Therefore in this project, we will be showing you our results using visuals aimed at delivering information efficiently and provocatively.
Questions we asked ourselves : ⁃As a citizen, how to act in order to reduce our CO2 emissions? ⁃Where are we today, in our city, in terms of CO2 emissions? ⁃What are the impact of various agreements or simple actions on CO2 emissions? ⁃Which cities are showing us the way to rapid decarbonization?
The outcomes we are aiming at :
- Change behaviors
- Raise awareness
- Empower decision making
Our steps :
⁃Highlight cities that are proactive in their climate decisions and visible improvement. ⁃Understand how they enacted. ⁃Point out the politics. ⁃And finally offer visualisation of how impactful these policies were to influence the others.
We Built It with
Python Pandas library (Data Cleaning), Python Dash library (Platform Creation and Data visualisation) and Heroku for app hosting.
What Challenged Us
We did struggle a lot to find datasets, clean our original dataset and find innovative ways to communicate our data.
What we are proud of
We are proud of first taking part in this amazing challenge, which forced us to surpass ourselves and adapt to challenges that go beyond our capacities and skillsets.
What we learnt
Climate data is incomplete and urging for us to use its potential in supporting a more positive approach when building the future bricks of our cities.