Challange Website: http://www.shl-dataset.org/activity-recognition-challenge-2021/
Team Name: GPU Kaj Kore Na
Team Members:
Abstract:
The Sussex-Huawei Locomotion-Transportation (SHL) recognition Challenge 2021 was a competition to classify 8 different activities and modes of locomotion performed by three individual users. There were four different modalities of data (Location, GPS, WiFi, and Cells) which were recorded from the phones of the users in their hip position. The train set came from user-1 and the validation set and test set were from user-2 and user-3. Our team ’GPU Kaj Kore Na’ used only location modality to give our predictions in test set of this year’s competition as location data was giving more accurate predictions and the rest of the modalities were too noisy as well as not contributing much to increase the accuracy. In our method, we used statistical feature set for feature extraction and Random Forest classifier to give prediction. We got validation accuracy of 78.138% and a weighted F1 score of 78.28% on the SHL Validation Set 2021.
Figure: Block Diagram of Our Method
Full Paper Link: https://dl.acm.org/doi/10.1145/3460418.3479376