An Approach of Using Contexts for In-home Activity Recognition and Forecast

被引：0

作者：

Tien Le ^{[1
]}

Duy Nguyen ^{[2
]}

Son Nguyen ^{[3
]}

机构：

[1] VNU, IU, Sch Engn & Comp Sci, Ho Chi Minh City, Vietnam

[2] Binh Duong Univ, Bolt Inst, Dept Informat Technol, Thu Dau Mot City, Binh Duong Prov, Vietnam

[3] VNU, UIT, Dept Comp Engn, Ho Chi Minh City, Vietnam

来源：

PROCEEDINGS OF 2016 THE 2ND INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND ROBOTICS | 2016年

关键词：

Smart home; activity recognition; activity forecast; in-home contexts; sensor systems;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Smart home is one of the most important applications of ubiquitous computing. In this work, we propose an infrastructure of Vietnamese Smart homes as well as a training framework for activity recognition and forecast. In this framework, active learning technique is applied and a new mining algorithm is proposed. In addition to activity recognition, a forecast mechanism is also added into the smart home simulation system by using activity sequence as an extra type of in-home contexts. Experiment results show that the system efficiency is improved when compared to the previous work of Enamul Hoque et al.

引用

页码：182 / 186

页数：5

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