The behavioral profiling based on times series forecasting for smart homes assistance

被引：13

作者：

Moutacalli, Mohamed Tarik ^{[1
]}

Bouzouane, Abdenour ^{[1
]}

Bouchard, Bruno ^{[1
]}

机构：

[1] UQAC, Dept Informat, Chicoutimi, PQ, Canada

来源：

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING | 2015年 / 6卷 / 05期

关键词：

Assisted living; Domestic care; Activity recognition; Activity detection; Activity prediction; Frequent pattern mining; Time series prediction; Smart homes;

D O I：

10.1007/s12652-015-0281-z

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The many disadvantages of traditional assistance available to elderly and persons with cognitive dysfunction such as patients with Alzheimer's disease have motivated the research of Technological assistance. The artificial agent, who will support the caregiver, is equipped with hardware and software resources that enable it to observe, analyze, infer and support, when needed, the assisted person. In this paper, we present the various stages of Technological assistance and propose a new algorithm for the step of activities models detection. We also explore an activity prediction step using time series. The experiments were conducted on real data recorded at LIARA smart home and the results are satisfactory.

引用

页码：647 / 659

页数：13

共 20 条

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