WePlog

Client Application

The mobile application shows a colored map of the user's current location, where the colors help indicate which street segments have been already picked clean (green) and which would need more work (red). These colors are provided by taking into account sessions from previous users and parameters per street. When starting a session, a plogger can activate the app like you would on Strava, and it will record the activity in the background.

Users can also post notes and pictures that are being sent to the city administrators. This way we seek to improve communication between the community and local governments. We also introduced gamification, ploggers can gain points by cleaning streets and doing more sessions, these points can later be traded for rewards and recognition.

Technical challenges

The challenge in this project lies in scoring streets or street segments based on raw longitude / latitude coordinates that are coming in from the mobile app. To tackle this challenge we first imported OpenStreetMap data to be able to go down to the street segment level. We used a PostgreSQL database powered by PostGIS to handle the GeoSpatial data.

We created a scoring algorithm that for each raw data point, snaps these coordinates to one of the imported street segments. Then, for each segment, it analyses these snapped locations from different users together with segment specific parameters to eventually give each segment a cleanliness score, that is used to color the map.

Some of these parameters, such as time intervals (some streets need to be cleaned more often than others) can be set manually using the admin dashboard. However we plan to optimise these parameters automatically based on user feedback on their routes using supervised machine learning techniques in the future.