DocumentCode :
3316971
Title :
Information Quality Management in Sensor Networks based on the Dynamic Bayesian Network model
Author :
Tolstikov, Andrei ; Xiao, Wendong ; Biswas, Jit ; Zhang, Sen ; Tham, Chen-Khong
Author_Institution :
Nat. Univ. of Singapore, Singapore
fYear :
2007
fDate :
3-6 Dec. 2007
Firstpage :
751
Lastpage :
756
Abstract :
To satisfy application information quality (IQ) constraints in a sensor network, the efficient way is to choose the most appropriate sensor nodes and sensor modalities which would provide a required IQ for the current state of the system. In this paper, two formulations of an activity recognition application are considered - the first based on static Bayesian network (BN), and the second on dynamic Bayesian network (DBN) which allows temporal changes to the conditional probabilities of the system states. It is shown that for similar results, in the certainty of state estimation, the formulation based on DBN uses much less resources, because it relies significantly on the readings obtained in the past. Also DBN model is more robust since it greatly reduces the likelihood of selecting unnaturally drastic state changes.
Keywords :
belief networks; sensor fusion; activity recognition; dynamic Bayesian network model; information quality management; sensor modalities; sensor networks; sensor nodes; state estimation; static Bayesian network; Acoustic sensors; Bayesian methods; Computer networks; Intelligent sensors; Monitoring; Multimodal sensors; Quality management; Sensor phenomena and characterization; Sensor systems; Sensor systems and applications;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information, 2007. ISSNIP 2007. 3rd International Conference on
Conference_Location :
Melbourne, Qld.
Print_ISBN :
978-1-4244-1501-4
Electronic_ISBN :
978-1-4244-1502-1
Type :
conf
DOI :
10.1109/ISSNIP.2007.4496937
Filename :
4496937
Link To Document :
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