A Bayesian network and rule-base approach towards activity inference

Venet Osmani, Sasitharan Balasubramaniam, Dmitri Botvich

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

In this paper we describe an activity recognition system capable of monitoring user activities in home environments. Activities are monitored by processing information from various sensors embedded in the environment that provide information pertinent to user's actions. We utilise the concept of self-organising Object Networks to gather and hierarchically process information related to user actions in a distributed manner. This information is then fed to the Decision Module which matches this information in the user's Activity Map in order to deduce user's activity. The Decision Module comprises a Bayesian Network coupled with a rule-based engine which is used to provide accurate activity inference process.

Original languageEnglish
Title of host publication2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall
Pages254-258
Number of pages5
DOIs
Publication statusPublished - 2007
Event2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall - Baltimore, MD, United States
Duration: 30 Sep 200703 Oct 2007

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Conference

Conference2007 IEEE 66th Vehicular Technology Conference, VTC 2007-Fall
Country/TerritoryUnited States
CityBaltimore, MD
Period30/09/200703/10/2007

Keywords

  • Activity inference
  • Activity recognition
  • Bayesian networks

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