Dataset: Channel State Information for Different Activities, Participants and Days

Jeroen Klein Brinke*, Nirvana Meratnia

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    Abstract

    In our current society, unobtrusive sensing has become an important tool to monitor the physical world, as it is easy to use and privacy-aware. Remote sensing is a new and heavily researched technology based on the analysis of radio signals. A particular field research in this area is the analysis of channel state information with the raw signal, as this contains the most information. While most research focuses on analysis of individuals or clustered data, little to no research has gone into the analysis of channel state information of multiple people over multiple days for different and comparable activities. This dataset contains data of nine different participants over three different days, with an two participants repeating the activities over an additional three days. The dataset is available at the 4TU.ResearchData under the CC BY-NC-SA license.
    Original languageEnglish
    Title of host publicationDATA’19
    Subtitle of host publicationProceedings of the Second Workshop on Data Acquisition To Analysis
    Place of PublicationNew York, NY
    PublisherACM Press
    Pages61-64
    Number of pages4
    ISBN (Print)978-1-4503-6993-0
    DOIs
    Publication statusPublished - 10 Nov 2019
    Event2nd Workshop on Data Acquisition To Analysis, DATA 2019 - New York, United States
    Duration: 10 Nov 201910 Nov 2019
    Conference number: 2

    Conference

    Conference2nd Workshop on Data Acquisition To Analysis, DATA 2019
    Abbreviated titleDATA
    CountryUnited States
    CityNew York
    Period10/11/1910/11/19

    Fingerprint

    Channel state information
    Remote sensing

    Keywords

    • Datasets
    • Channel state information
    • Human activity recognition
    • Device-free sensing
    • 802.11n
    • Data stability

    Cite this

    Klein Brinke, J., & Meratnia, N. (2019). Dataset: Channel State Information for Different Activities, Participants and Days. In DATA’19: Proceedings of the Second Workshop on Data Acquisition To Analysis (pp. 61-64). New York, NY: ACM Press. https://doi.org/10.1145/3359427.3361913
    Klein Brinke, Jeroen ; Meratnia, Nirvana . / Dataset: Channel State Information for Different Activities, Participants and Days. DATA’19: Proceedings of the Second Workshop on Data Acquisition To Analysis. New York, NY : ACM Press, 2019. pp. 61-64
    @inproceedings{c99c172edace473695519e34a4fe1e03,
    title = "Dataset: Channel State Information for Different Activities, Participants and Days",
    abstract = "In our current society, unobtrusive sensing has become an important tool to monitor the physical world, as it is easy to use and privacy-aware. Remote sensing is a new and heavily researched technology based on the analysis of radio signals. A particular field research in this area is the analysis of channel state information with the raw signal, as this contains the most information. While most research focuses on analysis of individuals or clustered data, little to no research has gone into the analysis of channel state information of multiple people over multiple days for different and comparable activities. This dataset contains data of nine different participants over three different days, with an two participants repeating the activities over an additional three days. The dataset is available at the 4TU.ResearchData under the CC BY-NC-SA license.",
    keywords = "Datasets, Channel state information, Human activity recognition, Device-free sensing, 802.11n, Data stability",
    author = "{Klein Brinke}, Jeroen and Nirvana Meratnia",
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    Klein Brinke, J & Meratnia, N 2019, Dataset: Channel State Information for Different Activities, Participants and Days. in DATA’19: Proceedings of the Second Workshop on Data Acquisition To Analysis. ACM Press, New York, NY, pp. 61-64, 2nd Workshop on Data Acquisition To Analysis, DATA 2019, New York, United States, 10/11/19. https://doi.org/10.1145/3359427.3361913

    Dataset: Channel State Information for Different Activities, Participants and Days. / Klein Brinke, Jeroen ; Meratnia, Nirvana .

    DATA’19: Proceedings of the Second Workshop on Data Acquisition To Analysis. New York, NY : ACM Press, 2019. p. 61-64.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    AB - In our current society, unobtrusive sensing has become an important tool to monitor the physical world, as it is easy to use and privacy-aware. Remote sensing is a new and heavily researched technology based on the analysis of radio signals. A particular field research in this area is the analysis of channel state information with the raw signal, as this contains the most information. While most research focuses on analysis of individuals or clustered data, little to no research has gone into the analysis of channel state information of multiple people over multiple days for different and comparable activities. This dataset contains data of nine different participants over three different days, with an two participants repeating the activities over an additional three days. The dataset is available at the 4TU.ResearchData under the CC BY-NC-SA license.

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    Klein Brinke J, Meratnia N. Dataset: Channel State Information for Different Activities, Participants and Days. In DATA’19: Proceedings of the Second Workshop on Data Acquisition To Analysis. New York, NY: ACM Press. 2019. p. 61-64 https://doi.org/10.1145/3359427.3361913