The Sussex-Huawei Locomotion Dataset will be used in an activity recognition challenge with results to be presented at the HASCA Workshop at Ubicomp 2019.
The goal of this machine learning/data science challenge was to recognize 8 modes of locomotion and transportation (activities) from the inertial sensor data of a smartphone. The dataset used for this challenge comprises 271 hours of training data and 95 hours of test data, from a single phone on a single user.
Here the results (F1 scores) of the top 5 teams:
- JSI-Deep: 93.86%
- JSI-Classic: 92.41%
- Tesaguri: 88.83%
- S304: 87.46%
- Confusion Matrix: 87.45%