Forecasting the behavior of an elderly using wireless sensors data in a smart home

被引：182
|
作者：
Suryadevara, N. K. [1 ]
Mukhopadhyay, S. C. [1 ]
Wang, R. [1 ]
Rayudu, R. K. [2 ]
机构：
[1] Massey Univ, Palmerston North, New Zealand
[2] Victoria Univ Wellington, Wellington, New Zealand
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2013年 / 26卷 / 10期
关键词：
Wireless Sensor Network; Smart home; Activity recognition; Activities of daily living; Elder care; Time series analysis; ACTIVITY RECOGNITION; CARE;
D O I：
10.1016/j.engappai.2013.08.004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the ability to determine the wellness of an elderly living alone in a smart home using a low-cost, robust, flexible and data driven intelligent system is presented. A framework integrating temporal and spatial contextual information for determining the wellness of an elderly has been modeled. A novel behavior detection process based on the observed sensor data in performing essential daily activities has been designed and developed. The developed prototype is used to forecast the behavior and wellness of the elderly by monitoring the daily usages of appliances in a smart home. Wellness models are tested at various elderly houses, and the experimental results are encouraging. The wellness models are updated based on the time series analysis. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2641 / 2652
页数：12
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