This project was created as a completion project of K136 Data Science Bootcamp, jointly organized by İstanbul Metropolitan Municipality (İBB), İstanbul Planning Agency, Data Laboratory, Enstitü İstanbul İsmek and Kodluyoruz. Thank you to all the supporters for all their support. And also special thanks to our trainer Mert Türkyılmaz (Linkedin) and valuable bootcamp assistants.
İsbike is the shared bicycle system provided by the İstanbul Metropolitan Municipality. Within the scope of this project, our goal was to determine with artificial intelligence algorithms in which locations the most suitable İsbike stations should be built for the Kadıköy district of İstanbul, which we chose as the pilot region. For this, we decided that using the K-means clustering algorithm would give the most appropriate results.
The data we used within the scope of the project were:
- Information on existing and planned bicycle paths in İstanbul has been provided by İstanbul Metropolitan Municipality (İBB) in geodatabase format.
- Polygon data of Kadıköy district's neighborhood boundaries, public transportation, green space, educational institutions, shopping centers, neighborhood centers were captured in geojson format via Open Street Map (OSM) API.
- İsbike Points - Obtained from the İBB open data portal in .csv format over the relevant API.
- The populations of the districts of Kadıköy were drawn from TUİK.
We wrote the codes in a functional way, and if desired, the necessary codes for different districts can be easily added. These codes can be used not only for İstanbul, but for any location in the world with suitable conditions. It can even be used for shared electric scooters with a few modifications if desired.
Team members involved in the project:
- İzel Çelikkaya - Linkedin - Github
- Uğur Can Kıvanç - Linkedin - Github
- Fuat Akdemir - Linkedin - Github - Website
- Kumru Orkun - Linkedin - Github
- Dursun Tunahan Bilgin - Linkedin - Github
For any question, you can contact us.