Title :
Managing context data for smart spaces
Author :
Castro, Paul ; Munz, R.
Author_Institution :
Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA
fDate :
10/1/2000 12:00:00 AM
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;
Journal_Title :
Personal Communications, IEEE
