The data mining and pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties in living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track activities that people normally perform as part of their daily routines. One question that frequently arises, however, is how many smart home sensors are needed and where should they be placed in order to accurately recognize activities? We employ data mining techniques to look at the problem of sensor selection for activity recognition in smart homes. We analyze the results based on six datasets collected in five distinct smart home environments. (C) 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 339-351 DOI:10.1002/widm.20
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机译：智能家庭中发现的数据挖掘和普及传感技术为为在家中独立生活困难的个人提供健康监测和帮助提供了前所未有的机会。为了监视智能家居居民的功能健康，我们需要设计技术来识别和跟踪人们通常在日常生活中执行的活动。但是，经常出现的一个问题是，需要多少个智能家居传感器，以及应该将它们放置在什么位置才能准确识别活动？我们采用数据挖掘技术来研究智能家居中用于活动识别的传感器选择问题。我们基于在五个不同的智能家居环境中收集的六个数据集来分析结果。 （C）2011 John Wiley＆Sons，Inc. WIREs Data Mining Knowl Discov 2011 1 339-351 DOI：10.1002 / widm.20
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