DocumentCode :
2230292
Title :
The Role of Probabilistic Schemes in Multisensor Context-Awareness
Author :
Dargie, Waltenegus
Author_Institution :
Dept. of Comput. Networks, Dresden Tech. Univ.
fYear :
2007
fDate :
19-23 March 2007
Firstpage :
27
Lastpage :
32
Abstract :
This paper investigates the role of existing "probabilistic" schemes to reason about various everyday situations on the basis of data from multiple heterogeneous physical sensors. The schemes we discuss are fuzzy logic, hidden Markov models, Bayesian networks, and Dempster-Schafer theory of evidence. The paper also presents a conceptual architecture and identifies the suitable scheme to be employed by each component of the architecture. As a proof-of-concept, we will introduce the architecture we implemented to model various places on the basis of data from temperature, light intensity and relative humidity sensors
Keywords :
belief networks; fuzzy logic; hidden Markov models; probability; sensor fusion; Bayesian networks; Dempster-Schafer theory; fuzzy logic; hidden Markov models; multisensor context-awareness; probabilistic schemes; Bayesian methods; Computer architecture; Computer networks; Context-aware services; Fuzzy logic; Hidden Markov models; Humans; Humidity; Sensor phenomena and characterization; Temperature sensors; Context; Context Modelling; Context Reasoning; Context-Aware Computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Communications Workshops, 2007. PerCom Workshops '07. Fifth Annual IEEE International Conference on
Conference_Location :
White Plains, NY
Print_ISBN :
0-7695-2788-4
Type :
conf
DOI :
10.1109/PERCOMW.2007.115
Filename :
4144788
Link To Document :
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