NEW: BikeVibes' demo has been accepted at 15th Intl Workshop on Computational Transportation Science (IWCTS 2022), co-located with the 30th ACM SIGSPATIAL Intl. Conf. on Advances in Geographic Information Systems (ACM SIGSPATIAL 2022). You can find the paper here.

BikeVibes is a research-based project at the University of Alberta's Department of Computing Science executed by Kai Luedemann under Mario Nascimento's supervision. 

The two main goals of the project at this stage are: (1) to build an Android-based app that people can use to record how "bumpy" their bicycle ride is, and, (2) to generate anonymized data that can be made freely available for others to build upon.  (The "data download" facility is under construction.)

The generated (open) data can be used, for instance,  by cities to identify streets that need repair, or to suggest "smooth" routes which could be interesting for people towing bike attachments with children. Another use could be identifying popular bike paths during different times of the year, or even during the day.

The app is currently available for open testing on the Google Play Store. The source code for the BikeVibes app and website can be viewed on GitHub.

Acknowledgements: K. Luedemann was been supported by an NSERC Undergraduate Student Research Award grant in the Summer/2022. The computational infrastructure for the project has been graciously provided by Cybera in Alberta.