Supporting pervasive computing applications with active context fusion and semantic context delivery

Nirmalya Roy, Tao Gu, Sajal K. Das

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

Future pervasive computing applications are envisioned to adapt the applications’ behaviors by utilizing various contexts of an environment and its users. Such context information may often be ambiguous and also heterogeneous, which make the delivery of unambiguous context information to real applications extremely challenging. Thus, a significant challenge facing the development of realistic and deployable context-aware services for pervasive computing applications is the ability to deal with these ambiguous contexts. In this paper, we propose a resource optimized quality assured context mediation framework based on efficient context-aware data fusion and semantic-based context delivery. In this framework, contexts are first fused by an active fusion technique based on Dynamic Bayesian Networks and ontology, and further mediated using a composable ontological rule-based model with the involvement of users or application developers. The fused context data are then organized into an ontology-based semantic network together with the associated ontologies in order to facilitate efficient context delivery. Experimental results using SunSPOT and other sensors demonstrate the promise of this approach.

Original languageEnglish
Pages (from-to)21-42
Number of pages22
JournalPervasive and Mobile Computing
Volume6
Issue number1
DOIs
Publication statusPublished - Feb 2010
Externally publishedYes

Keywords

  • Pervasive computing
  • Context awareness
  • Context fusion
  • Bayesian networks
  • Ontology
  • SunSPOT

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