Winner of the 2019 Climathon Heidelberg

Over the last few days, Heidelberg’s first climathon event took place at EMBL, which was part of the global Climathon. The event ran from 25th-27th October 2019 with a 24 hour hackathon taking place on the 26th-27th. During the 24 hours developers, entrepreneurs, designers and students came together and worked as teams on 5 innovative challenges, all with an aspect of addressing climate change.

The first place was awarded to the BikeBuddy and Spring Up teams. We are happy to announce that both winning teams comprised members from the GIScience research group Heidelberg.

The BikeBuddy team worked on a challenge presented by HeiGIT which challenged to identify attractive cycling routes to encourage people to use bikes rather than cars. This was inspired by the research on pleasant routing at GIScience/HeiGIT. The main factor that the team focused on was the safety of cyclist routes. In this context, streets that are not lit at night were considered as being less safe, and so should be avoided during route calculation. Furthermore tram track data was identified that might help cyclists to avoid bike lanes close to tram tracks. The data was extracted from OpenStreetMap.

The other winning team (Spring Up) created a concept to visualize the effect of climate change on local plants. The solution included a gaming app where anyone is encouraged to locate blooming plants. Afterwards, the blooming timing can be compared locally with scientific blooming models through which users can realize the change of micro-climates.

Further the popular award which was voted by the participants themselves went to the „Klima zum Anfassen“ team. This team implemented an application which showed the effect of the climate change on public displays. In doing so, people should become more aware of their actions.

Congratulation to all the winner teams, and a big thank you to the organizers!

©Theodore Alexandrov

©Theodore Alexandrov

Novack, T.; Wang, Z.; Zipf, A. (2018): A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data. Sensors 2018, 18, 3794.

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