Sussex-Huawei Locomotion Challenges

Challenge 2019

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.

Challenge 2018

The Sussex-Huawei Locomotion Dataset was used in the first edition of an activity recognition challenge of the same name. The results were presented at the HASCA Workshop at Ubicomp 2018.

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%