PowerFX

Inspiration

Invest Windsor Essex wants to speed up the transition from conventional gas vehicles to zero-emission vehicles which help to protect the environment. In order to do that, they’re looking for ways to optimize the availability of electric vehicle chargers in the region.

What it does

Our app allows us to place custom markers for electric chargers on the map where they can be installed in the future. Additionally, it also helps us to look at existing charging stations in Windsor so that the user can navigate to their nearest power point. Using machine learning we can also predict whether a location is suitable to have a public charging station or not.

How we built it

• The app is built using Flutter
• Data Analysis and prediction has been done using Python using libraries such as geopandas, sklearn etc

Challenges we ran into

• Integrating google maps with custom pointers in Flutter
• Utilising geolocation as a feature for machine learning prediction

Accomplishments that we're proud of

• Learned to develop apps through flutter workshop
• Got to know Open Street Maps and geospatial machine learning

What we learned

• Using maps and associated machine learning techniques
• Debugging flutter apps

What's next for PowerFX

• Complete our prediction model with real charging station data and integrate the model into our app

Built With

• dart
• flutter
• geopandas
• google-maps
• machine-learning
• python