Where Are You? Human Activity Recognition with Smartphone Sensor Data

被引：7

作者：

Dogan, Gulustan ^{[1
]}

Cay, Iremnaz ^{[2
]}

Ertas, Sinem Sena ^{[2
]}

Keskin, Seref Recep ^{[3
]}

Alotaibi, Nouran ^{[1
]}

Sahin, Elif ^{[1
]}

机构：

[1] Univ North Carolina Wilmington, Wilmington, NC 28403 USA

[2] Istanbul Sabahattin Zaim Univ, Istanbul, Turkey

[3] Gazi Univ, Ankara, Turkey

来源：

UBICOMP/ISWC '20 ADJUNCT: PROCEEDINGS OF THE 2020 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2020 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS | 2020年

关键词：

Activity Recognition; Locomotion Classification; Transportation Mode Prediction; Machine Learning;

D O I：

10.1145/3410530.3414354

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes our submission as Team-Petrichor to the competition that was organized by the SHL recognition challenge dataset authors. We compared multiple machine learning approach for classifying eight different activities (Still, Walk, Run, Bike, Car, Bus, Train, Subway). The first step was feature engineering, a wide set of statistical domain features were computed and their quality was evaluated. Finally, the appropriate machine learning model was chosen. The recognition result for the testing dataset will be presented in the summary paper of the SHL recognition challenge.

引用

页码：301 / 304

页数：4

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