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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/108946

    题名: A New Habit Pattern Learning Scheme in Smart Home
    作者: Wang, Pingquan;Luo, Hong;Li, Xinming;Zhao, Zhongwen
    关键词: Smart Home;Habit Pattern;Time Series;Activity Recognition
    日期: 2016-03
    上传时间: 2016-12-20 09:46:51 (UTC+8)
    出版者: 淡江大學出版中心
    摘要: Most of the user’s activities are consistent with their habits, therefore in this paper, we propose
    a new habit pattern learning scheme in smart home to better obtain user’s behavior regulations and
    habits, which can make the home more intellectually interact with people. By recording the operations
    on each electric appliance in the form of time series, we firstly find out that the habit can be classified
    into fixed-length habit and timing habit. Then, we propose habit extraction methods based on the
    corresponding activity probability and calculation formulas of the habit strength. Since different habits
    have different variation characteristics on habit strength and time zone, we further propose the
    self-learning algorithms on time zone and habit strength threshold to obtain the suitable parameters.
    Furthermore, by defining the association among individual habits into selection, parallel, sequence,
    cross and inclusion, we can obtain habit set which is a group of habits with inner correlation. In order to
    adapt to the habit variations, we introduce a habit change factor into the habit pattern discovery
    algorithm so as to follow the habit changes. Finally, we construct the experimental environment in a
    real smart home, analyze and calculate the operation records of electric appliances in two months. The
    experiment results show that the proposed habit pattern learning scheme is effective and efficient.
    關聯: Journal of Applied Science and Engineering 19(1), pp.83-94
    DOI: 10.6180/jase.2016.19.1.10
    显示于类别:[淡江理工學刊] 第19卷第1期


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