A Multilayered Uncertainty Model for Context Aware Systems

Susan McKeever; Juan Ye; Lorcan Coyle; Simon Dobson

doi:10.21427/gqs6-xf45

A Multilayered Uncertainty Model for Context Aware Systems

Susan McKeever, Juan Ye, Lorcan Coyle, Simon Dobson

School of Computer Science

Research output: Contribution to conference › Paper › peer-review

Abstract

Context-aware systems typically use data sensed from the environment to drive adaptive behaviour. Sensed data is inherently imprecise and uncertain: in addition, new uncertainties are introduced when sensed data is fused with other data to infer context at the more abstract level of situations. We present an uncertainty model which aggregates context uncertainty and provides mechanisms to capture uncertainty at situation level. We demonstrate the application of the model in a sample scenario using an experimental data set

Original language	English
DOIs	https://doi.org/10.21427/gqs6-xf45
Publication status	Published - 2008
Event	Pervasive 2008 Late Breaking Results - Sydney, Australia Duration: 1 Jan 2008 → …

Conference

Conference	Pervasive 2008 Late Breaking Results
Country/Territory	Australia
City	Sydney
Period	1/01/08 → …

Keywords

Context-aware systems
sensed data
imprecise
uncertain
context uncertainty
situation level
experimental data set

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10.21427/gqs6-xf45Licence: CC BY-NC-SA

Cite this

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AU - Ye, Juan

AU - Coyle, Lorcan

AU - Dobson, Simon

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N2 - Context-aware systems typically use data sensed from the environment to drive adaptive behaviour. Sensed data is inherently imprecise and uncertain: in addition, new uncertainties are introduced when sensed data is fused with other data to infer context at the more abstract level of situations. We present an uncertainty model which aggregates context uncertainty and provides mechanisms to capture uncertainty at situation level. We demonstrate the application of the model in a sample scenario using an experimental data set

AB - Context-aware systems typically use data sensed from the environment to drive adaptive behaviour. Sensed data is inherently imprecise and uncertain: in addition, new uncertainties are introduced when sensed data is fused with other data to infer context at the more abstract level of situations. We present an uncertainty model which aggregates context uncertainty and provides mechanisms to capture uncertainty at situation level. We demonstrate the application of the model in a sample scenario using an experimental data set

KW - Context-aware systems

KW - sensed data

KW - imprecise

KW - uncertain

KW - context uncertainty

KW - situation level

KW - experimental data set

U2 - 10.21427/gqs6-xf45

DO - 10.21427/gqs6-xf45

M3 - Paper

T2 - Pervasive 2008 Late Breaking Results

Y2 - 1 January 2008

ER -

A Multilayered Uncertainty Model for Context Aware Systems

Abstract

Conference

Keywords

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