Using Smartwatch Inertial Sensors to Recognize and Distinguish Between Car Drivers and Passengers

Thomas Cano Hald, David Holmgaard Junker, Mads Mårtensson, Mikael Skov, Dimitrios Raptis

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6 Citationer (Scopus)

Abstract

People increasingly interact with social media or other apps on their smartphones while driving car. This is naturally a major safety concern, and it remains unclear how to avoid or limit such interaction. We investigate this problem through human activity recognition (HAR) where we developed a system called IRIS, which collects smartwatch accelerometer data and analyses the data through machine learning and predicts if the data origins from a driver or a passenger. We report from a field experiment with 24 participants acting as drivers or passengers where we achieved an overall prediction accuracy of 87%. We further found that various road segments had less effect on the accuracy than anticipated, but we also found that passenger tasks had a negative effect on recognition accuracy. We discuss several implications from findings.
OriginalsprogEngelsk
TitelProceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Antal sider11
ForlagAssociation for Computing Machinery
Publikationsdato23 sep. 2018
Sider74-84
ISBN (Elektronisk)978-1-4503-5946-7
DOI
StatusUdgivet - 23 sep. 2018
Begivenhed10th International ACM Conference on Automotive User Interfaces - Toronto, Canada
Varighed: 23 sep. 201825 sep. 2018

Konference

Konference10th International ACM Conference on Automotive User Interfaces
Land/OmrådeCanada
ByToronto
Periode23/09/201825/09/2018

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