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

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.