A unified framework for activity recognition-based behavior analysis and action prediction in smart homes

Iram Fatima, Muhammad Fahim, Young Koo Lee*, Sungyoung Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)

Abstract

In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users" actions to gain knowledge about their habits and preferences.

Original languageEnglish
Pages (from-to)2682-2699
Number of pages18
JournalSensors (Switzerland)
Volume13
Issue number2
DOIs
Publication statusPublished - 22 Feb 2013
Externally publishedYes

Bibliographical note

Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.

Keywords

  • Action prediction
  • Activity recognition
  • Behavior analysis
  • Lifestyle analysis
  • Smart homes
  • U-healthcare

ASJC Scopus subject areas

  • Artificial Intelligence
  • Electrical and Electronic Engineering

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