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

Published: 23 September 2018 Publication History

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.

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  • (2024)An Automated Smartphone-Capable Road Traffic Accident Notification SystemJournal of Advanced Computational Intelligence and Intelligent Informatics10.20965/jaciii.2024.p093928:4(939-952)Online publication date: 20-Jul-2024
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  • (2022)A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature ReviewProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35346176:2(1-51)Online publication date: 7-Jul-2022
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    cover image ACM Conferences
    AutomotiveUI '18: Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
    September 2018
    374 pages
    ISBN:9781450359467
    DOI:10.1145/3239060
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 23 September 2018

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    Author Tags

    1. Smartwatch
    2. accelerometer data
    3. driving
    4. human activity recognition
    5. sensor data

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    View all
    • (2024)An Automated Smartphone-Capable Road Traffic Accident Notification SystemJournal of Advanced Computational Intelligence and Intelligent Informatics10.20965/jaciii.2024.p093928:4(939-952)Online publication date: 20-Jul-2024
    • (2024)Internet of robotic things for independent living: Critical analysis and future directionsInternet of Things10.1016/j.iot.2024.10112025(101120)Online publication date: Apr-2024
    • (2022)A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature ReviewProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35346176:2(1-51)Online publication date: 7-Jul-2022
    • (2020)Computational Offloading of Convolutional Neural Network on a Smart Watch2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)10.1109/ICAIIC48513.2020.9064970(203-207)Online publication date: Feb-2020
    • (2020)Computational Offloading for CNN-based Toxic Comment Detection on a Smartwatch2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC)10.1109/FMEC49853.2020.9144770(284-288)Online publication date: Apr-2020
    • (2019)From Manual Driving to Automated DrivingProceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3342197.3344529(70-90)Online publication date: 21-Sep-2019
    • (2019)Smartwatches as IoT Edge Devices: A Framework and Survey2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)10.1109/FMEC.2019.8795338(216-222)Online publication date: Jun-2019

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