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tutorial

Motion Capture Using the Internet of Things Technology: A Tutorial

Published: 19 July 2017 Publication History
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  • Abstract

    This tutorial explores a variety of applications for Internet of Things (IoT) aided motion capture, drawing comparisons from different technologies and implementations. Various uses for these implementations will be discussed, as well as weighted against one another to analyse their advantages and disadvantages.

    References

    [1]
    Abdelrahman Abuarqoub, Mohammad Hammoudeh, Bamidele Adebisi, Sohail Jabbar, Ahcne Bounceur, and Hashem Al-Bashar. 2017. Dynamic clustering and management of mobile wireless sensor networks. Computer Networks 117 (2017), 62-75. Cyber-physical systems and context-aware sensing and computing.
    [2]
    Yasmin Ali. 2015. Motion capture improves animation of animals. http://www.bbc.co.uk/news/science-environment-34175225. (2015). {Online; accessed 8-June-2017}.
    [3]
    Sohail Jabbar, Murad Khan, Bhagya Nathali Silva, and Kijun Han. 2016. A RESTbased industrial web of things' framework for smart warehousing. The Journal of Supercomputing (2016), 1-15.
    [4]
    Sohail Jabbar, Abid Ali Minhas, Moneeb Gohar, Anand Paul, and Seungmin Rho. 2015. E-MCDA: Extended-Multilayer Cluster Designing Algorithm for Network Lifetime Improvement of Homogenous Wireless Sensor Networks. International Journal of Distributed Sensor Networks 11, 9 (2015), 902581.
    [5]
    Sohail Jabbar, Farhan Ullah, Shehzad Khalid, Murad Khan, and Kijun Han. 2017. Semantic interoperability in heterogeneous iot infrastructure for healthcare. Wireless Communications and Mobile Computing 2017 (2017).
    [6]
    Paul James. 2016. Hands On: Audi's Stunning Next-gen Showrooms are Powered by Vive and Rift. http://www.roadtovr.com/audi-virtual-reality-car-showroom-htc-vive-pre-oculus-rift-cv1/. (2016). {Online; accessed 12-June-2017}.
    [7]
    Murad Khan, Sadia Din, Sohail Jabbar, Moneeb Gohar, Hemant Ghayvat, and S.C. Mukhopadhyay. 2016. Context-aware low power intelligent SmartHome based on the Internet of things. Computers & Electrical Engineering 52 (2016), 208-222.

    Cited By

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    • (2019)Model Mediation to Overcome Light Limitations—Toward a Secure Tactile Internet SystemJournal of Sensor and Actuator Networks10.3390/jsan80100068:1(6)Online publication date: 2-Jan-2019
    • (2019)NeuronUnityIntegration2.0. A Unity Based Application for Motion Capture and Gesture RecognitionProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3350598(2199-2201)Online publication date: 15-Oct-2019

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    Published In

    cover image ACM Other conferences
    ICFNDS '17: Proceedings of the International Conference on Future Networks and Distributed Systems
    July 2017
    325 pages
    ISBN:9781450348447
    DOI:10.1145/3102304
    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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    • LABSTICC: Labsticc

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 19 July 2017

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    Author Tags

    1. Internet of Things
    2. Motion Capture
    3. Smart Suite
    4. Wearable Body Technology

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    Cited By

    View all
    • (2019)Model Mediation to Overcome Light Limitations—Toward a Secure Tactile Internet SystemJournal of Sensor and Actuator Networks10.3390/jsan80100068:1(6)Online publication date: 2-Jan-2019
    • (2019)NeuronUnityIntegration2.0. A Unity Based Application for Motion Capture and Gesture RecognitionProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3350598(2199-2201)Online publication date: 15-Oct-2019

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