@inproceedings{Schrapel:2020:MUM:Skiables,
	abstract = {Winter sports like skiing are becoming increasingly popular for both competitive and recreational activities. To minimize the risk of injury, new innovations in skiing equipment have been developed in recent years. However, unexpected slope conditions can still increase risks during skiing. The static categorisation of ski slopes in winter sports resorts does not take into account dynamic changes of difficulty due to high traffic volumes or sudden weather changes. Up to now, efforts have been made to measure the current conditions via satellite imaging or installations on the slope. However, this requires intervention in nature and causes high maintenance costs. To solve these issues we present our preliminary design of a wearable system to let skiers implicitly measure current slope conditions during their skiing experience. Audio and motion data are recorded from a prototype mounted on a ski boot. We show that the data generated by the prototype can be successfully classified with a neural network. We collected data from a skiing activity to demonstrate our concept and discuss the identified challenges in fitting the proposed approach to winter sports equipment.},
	title = {Skiables: Towards a Wearable System Mounted on a Ski Boot for Measuring Slope Conditions},
	author = {Schrapel, Maximilian and Liebers, Jonathan and Rohs, Michael and Schneegass, Stefan},
	booktitle = {19th International Conference on Mobile and Ubiquitous Multimedia},
	location = {Essen, Germany},
	doi = {10.1145/3428361.3432071},
	isbn = {9781450388702},
	year = {2020},
	papertype = {poster}
}