Managing context data for smart spaces

Author

Castro, Paul ; Munz, R.

Author_Institution

Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA

Volume

7

Issue

5

fYear

2000

fDate

10/1/2000 12:00:00 AM

Firstpage

44

Lastpage

46

Abstract

Describes our on-going efforts to construct a service infrastructure to support smart environments. We characterize “fusion services”, which extract and infer useful context information from sensor data, using evidential reasoning techniques. We specify sensing services as Bayesian networks and use information-theoretic algorithms to optimize the resources consumed by the rendering of a service. We define a “quality-of-information” metric to characterize sensing service performance. We have implemented an infrastructure for supporting a dynamic set of sensors and services in a smart space. Using this infrastructure and an IEEE 802.11 network, we implemented a probabilistic indoor location system that optimizes the number of sensors consulted when determining the location of a user while maintaining a high degree of accuracy

Keywords

belief networks; building management systems; case-based reasoning; mobile computing; quality of service; sensor fusion; Bayesian networks; IEEE 802.11 network; accuracy; context data management; context information; evidential reasoning techniques; fusion services; information quality metric; information-theoretic algorithms; probabilistic indoor location system; resource consumption optimization; sensing service performance; sensor data; sensor number optimization; service infrastructure; smart environments; smart spaces; user location determination; Bayesian methods; Context-aware services; Data mining; Entropy; Environmental management; Grounding; Intelligent sensors; Probability distribution; Sensor phenomena and characterization; Sensor systems;

fLanguage

English

Journal_Title

Personal Communications, IEEE

Publisher

ieee

ISSN

1070-9916

Type

jour

DOI

10.1109/98.878537

Filename

878537