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
收藏
页码：182 / 186
页数：5
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