Please use this identifier to cite or link to this item:
|Title:||Information quality management in sensor networks based on the dynamic Bayesian network model|
|Authors:||Tolstikov, A. |
|Source:||Tolstikov, A., Xiao, W., Biswas, J., Zhang, S., Tham, C.-K. (2007). Information quality management in sensor networks based on the dynamic Bayesian network model. Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP : 751-756. ScholarBank@NUS Repository. https://doi.org/10.1109/ISSNIP.2007.4496937|
|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. © 2007 IEEE.|
|Source Title:||Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2017
WEB OF SCIENCETM
checked on Nov 19, 2017
checked on Dec 17, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.