Modeling and analyzing individual's daily activities using lifelog

Katsuhiro Takata, Ma Jianhua, Bernady O. Apduhan, Runhe Huang, Qun Jin

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    14 Citations (Scopus)

    Abstract

    Lifelog is a data set composed of one or more media forms that record the same individual's daily activities. One of the main challenging issues is how to extract meaningful information from the huge and complex lifelog data which is continuously captured and accumulated from multiple sensors. This study is focused on the activity models and analysis techniques to process lifelog data in order: to find what events/states are interesting or important, to summarize the useful records in some structured and semantic ways for efficient retrievals and presentations of past life experiences, and to use these experiences to further improve the individual's quality of life. We propose an integrated technique to process the lifelog data using the correlations between different kinds of captured data from multiple sensors, instead of dealing with them separately. To use and test the proposed models and the analysis techniques, several prototype systems have been implemented and applied to some domain-specific lifelog data; such as in improving a group's collaborative efforts in revising a software, in managing kid's outdoor safety care, in providing a runner's workout assistance, and in structuring lifelog image generation, respectively.

    Original languageEnglish
    Title of host publicationProceedings of The International Conference on Embedded Software and Systems, ICESS 2008
    Pages503-510
    Number of pages8
    DOIs
    Publication statusPublished - 2008
    Event2008 International Conference on Embedded Software and Systems, ICESS-08 - Chengdu, Sichuan
    Duration: 2008 Jul 292008 Jul 31

    Other

    Other2008 International Conference on Embedded Software and Systems, ICESS-08
    CityChengdu, Sichuan
    Period08/7/2908/7/31

    Fingerprint

    Sensors
    Semantics

    ASJC Scopus subject areas

    • Hardware and Architecture
    • Software

    Cite this

    Takata, K., Jianhua, M., Apduhan, B. O., Huang, R., & Jin, Q. (2008). Modeling and analyzing individual's daily activities using lifelog. In Proceedings of The International Conference on Embedded Software and Systems, ICESS 2008 (pp. 503-510). [4595603] https://doi.org/10.1109/ICESS.2008.75

    Modeling and analyzing individual's daily activities using lifelog. / Takata, Katsuhiro; Jianhua, Ma; Apduhan, Bernady O.; Huang, Runhe; Jin, Qun.

    Proceedings of The International Conference on Embedded Software and Systems, ICESS 2008. 2008. p. 503-510 4595603.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Takata, K, Jianhua, M, Apduhan, BO, Huang, R & Jin, Q 2008, Modeling and analyzing individual's daily activities using lifelog. in Proceedings of The International Conference on Embedded Software and Systems, ICESS 2008., 4595603, pp. 503-510, 2008 International Conference on Embedded Software and Systems, ICESS-08, Chengdu, Sichuan, 08/7/29. https://doi.org/10.1109/ICESS.2008.75
    Takata K, Jianhua M, Apduhan BO, Huang R, Jin Q. Modeling and analyzing individual's daily activities using lifelog. In Proceedings of The International Conference on Embedded Software and Systems, ICESS 2008. 2008. p. 503-510. 4595603 https://doi.org/10.1109/ICESS.2008.75
    Takata, Katsuhiro ; Jianhua, Ma ; Apduhan, Bernady O. ; Huang, Runhe ; Jin, Qun. / Modeling and analyzing individual's daily activities using lifelog. Proceedings of The International Conference on Embedded Software and Systems, ICESS 2008. 2008. pp. 503-510
    @inproceedings{c5f371c7c4584f94b1f9371e04cf07ab,
    title = "Modeling and analyzing individual's daily activities using lifelog",
    abstract = "Lifelog is a data set composed of one or more media forms that record the same individual's daily activities. One of the main challenging issues is how to extract meaningful information from the huge and complex lifelog data which is continuously captured and accumulated from multiple sensors. This study is focused on the activity models and analysis techniques to process lifelog data in order: to find what events/states are interesting or important, to summarize the useful records in some structured and semantic ways for efficient retrievals and presentations of past life experiences, and to use these experiences to further improve the individual's quality of life. We propose an integrated technique to process the lifelog data using the correlations between different kinds of captured data from multiple sensors, instead of dealing with them separately. To use and test the proposed models and the analysis techniques, several prototype systems have been implemented and applied to some domain-specific lifelog data; such as in improving a group's collaborative efforts in revising a software, in managing kid's outdoor safety care, in providing a runner's workout assistance, and in structuring lifelog image generation, respectively.",
    author = "Katsuhiro Takata and Ma Jianhua and Apduhan, {Bernady O.} and Runhe Huang and Qun Jin",
    year = "2008",
    doi = "10.1109/ICESS.2008.75",
    language = "English",
    isbn = "9780769532875",
    pages = "503--510",
    booktitle = "Proceedings of The International Conference on Embedded Software and Systems, ICESS 2008",

    }

    TY - GEN

    T1 - Modeling and analyzing individual's daily activities using lifelog

    AU - Takata, Katsuhiro

    AU - Jianhua, Ma

    AU - Apduhan, Bernady O.

    AU - Huang, Runhe

    AU - Jin, Qun

    PY - 2008

    Y1 - 2008

    N2 - Lifelog is a data set composed of one or more media forms that record the same individual's daily activities. One of the main challenging issues is how to extract meaningful information from the huge and complex lifelog data which is continuously captured and accumulated from multiple sensors. This study is focused on the activity models and analysis techniques to process lifelog data in order: to find what events/states are interesting or important, to summarize the useful records in some structured and semantic ways for efficient retrievals and presentations of past life experiences, and to use these experiences to further improve the individual's quality of life. We propose an integrated technique to process the lifelog data using the correlations between different kinds of captured data from multiple sensors, instead of dealing with them separately. To use and test the proposed models and the analysis techniques, several prototype systems have been implemented and applied to some domain-specific lifelog data; such as in improving a group's collaborative efforts in revising a software, in managing kid's outdoor safety care, in providing a runner's workout assistance, and in structuring lifelog image generation, respectively.

    AB - Lifelog is a data set composed of one or more media forms that record the same individual's daily activities. One of the main challenging issues is how to extract meaningful information from the huge and complex lifelog data which is continuously captured and accumulated from multiple sensors. This study is focused on the activity models and analysis techniques to process lifelog data in order: to find what events/states are interesting or important, to summarize the useful records in some structured and semantic ways for efficient retrievals and presentations of past life experiences, and to use these experiences to further improve the individual's quality of life. We propose an integrated technique to process the lifelog data using the correlations between different kinds of captured data from multiple sensors, instead of dealing with them separately. To use and test the proposed models and the analysis techniques, several prototype systems have been implemented and applied to some domain-specific lifelog data; such as in improving a group's collaborative efforts in revising a software, in managing kid's outdoor safety care, in providing a runner's workout assistance, and in structuring lifelog image generation, respectively.

    UR - http://www.scopus.com/inward/record.url?scp=51849099391&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=51849099391&partnerID=8YFLogxK

    U2 - 10.1109/ICESS.2008.75

    DO - 10.1109/ICESS.2008.75

    M3 - Conference contribution

    AN - SCOPUS:51849099391

    SN - 9780769532875

    SP - 503

    EP - 510

    BT - Proceedings of The International Conference on Embedded Software and Systems, ICESS 2008

    ER -