Helps to decide where to plant trees in cities and parks based on one or more images.
- Noise reduction
- Air quality
- Aesthetics
- Mental health
- Community space
- Image (geotagged) and budget provided
- Images should look down the middle of street
- Images passed through API to Python function
- Images analysed and determines list of ideal pixels for new trees
- Assigned with score for improvement to area
- Program iteratively decides which trees are best for an area
- List of trees and images are returned to the interface
| Selection Criteria | Weighting |
|---|---|
| Existing trees / greenery | high |
| Types of building | medium |
| Street / pavement width | high |
| Parking spaces | medium |
| Nearby roads based on location | medium |
- Python (interacting with AI)
- OpenCV for image analysis
- JavaScript (API)
- React user interface
AI will be used to determine which type of trees are best for a situation and where to plant them, based on parameters in the image such as
- appearance of area
- space available (space could be made available by removing parking spaces)
- nearby roads (based on OpenStreetMap API and image geo-tag)
- types of buildings
It will also determine which areas will benefit most from trees based on a total budget provided for all the areas in the images.