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A System Designed to Collect Users' TV-Watching Data Using a Smart TV, Smartphones, and Smart Watches

Published: 17 June 2016 Publication History

Abstract

In this study, we suggest an enhanced smart TV logging system composed of a smart TV, smartphone, and smart watch. It can be used to research the audience's complicated and segmented behaviors while watching TV. We designed a prototype of the system, which can not only detect whether viewers are located in the TV-viewing area but also measure their movements and activities by analyzing beacon signals and sensor data from the smart watch. We conducted a technical evaluation to verify its fidelity and measure its performance, and a user study identified what factors affect the users' level of engagement with the TV content. The experiment results showed that the system accurately detected and measured users' location and engagement levels while watching TV. We found that smartphone usage while watching TV is important in understanding users' TV-viewing behavior.

References

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Abreu, Jorge, et al. "Viewer behaviors and practices in the (new) Television Environment." In Proc. on Interactive TV and video. ACM, 2013
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Bieber, Gerald, Marian Haescher, and Matthias Vahl. "Sensor requirements for activity recognition on smart watches." Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments. ACM, 2013.
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Case, Meredith A., et al. "Accuracy of smartphone applications and wearable devices for tracking physical activity data." Jama 313.6 (2015): 625--626.
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Feldmann, S., Kyamakya, K., Zapater, A., & Lue, Z. (2003, June). An Indoor Bluetooth-Based Positioning System: Concept, Implementation and Experimental Evaluation. In International Conference on Wireless Networks (pp. 109--113).
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Fujinami, Kaori, and Satoshi Kouchi. "Recognizing a Mobile Phone's Storing Position as a Context of a Device and a User." Mobile and ubiquitous systems: computing, networking, and services. Springer Berlin Heidelberg, 2012. 76--88.
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Harrison, Chris, Julia Schwarz, and Scott E. Hudson. "TapSense: enhancing finger interaction on touch surfaces." Proceedings of the 24th annual ACM symposium on User interface software and technology. ACM, 2011.
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RSSI, Wikipedia https://en.wikipedia.org/wiki/Received_signal_stre ngth_indication
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Seo, J., Kim, D., Suh, B., & Lee, J. (2015, April). Design of a Smart TV Logging System Using Beacons and Smartphones. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems (pp. 2157--2162). ACM.

Cited By

View all
  • (2023)SmartLog: A Smart TV-Based Lifelogging System for Capturing, Storing, and Visualizing Watching BehaviorInternational Journal of Human–Computer Interaction10.1080/10447318.2023.225005440:20(6232-6251)Online publication date: 29-Aug-2023
  • (2021)Smart TV-Based Lifelogging Systems: Current Trends, Challenges, and the Road AheadInformation and Knowledge in Internet of Things10.1007/978-3-030-75123-4_2(31-58)Online publication date: 7-Oct-2021
  • (2018)A Data-driven Approach to Explore Television Viewing in the Household EnvironmentProceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video10.1145/3210825.3210829(89-100)Online publication date: 25-Jun-2018
  • Show More Cited By

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    Published In

    cover image ACM Conferences
    TVX '16: Proceedings of the ACM International Conference on Interactive Experiences for TV and Online Video
    June 2016
    202 pages
    ISBN:9781450340670
    DOI:10.1145/2932206
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 17 June 2016

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    Author Tags

    1. beacon
    2. machine learning
    3. smart tv
    4. smart watch
    5. tv rating
    6. tv-watching behavior

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    Acceptance Rates

    TVX '16 Paper Acceptance Rate 12 of 38 submissions, 32%;
    Overall Acceptance Rate 69 of 245 submissions, 28%

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    Cited By

    View all
    • (2023)SmartLog: A Smart TV-Based Lifelogging System for Capturing, Storing, and Visualizing Watching BehaviorInternational Journal of Human–Computer Interaction10.1080/10447318.2023.225005440:20(6232-6251)Online publication date: 29-Aug-2023
    • (2021)Smart TV-Based Lifelogging Systems: Current Trends, Challenges, and the Road AheadInformation and Knowledge in Internet of Things10.1007/978-3-030-75123-4_2(31-58)Online publication date: 7-Oct-2021
    • (2018)A Data-driven Approach to Explore Television Viewing in the Household EnvironmentProceedings of the 2018 ACM International Conference on Interactive Experiences for TV and Online Video10.1145/3210825.3210829(89-100)Online publication date: 25-Jun-2018
    • (2018)Deep Learning Approach of Raw Human Activity DataChallenges of the Internet of Things10.1002/9781119549765.ch2(27-51)Online publication date: 12-Oct-2018
    • (2017)Study of the viewers' TV-watching behaviors before, during and after watching a TV program using iot network2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC.2017.8122886(1850-1855)Online publication date: 5-Oct-2017

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