An Intelligent System Based On Adaptive CTBN For Uncertainty Reasoning In Sensor Networks
Dongyu Shi, Xinhuai Tang, Jinyuan You · Intelligent Automation & Soft Computing · 2010
Abstract ;onsisting of various sensing and computing devices deployed in a changing environrnent, a sensor network’s raw sensed data have many uncertainties. A natural way to deal with them is generating belief messages. Sensing objects continuously change with time, so are their beliefs. Therefore, dynamic models are required to monitor distributed states in the system. This paper presents a CTBN based intelligent system for modeling dynamics and processing uncertainties in sensor networks. Algorithms for message passing and parameter updating for adapting the model to the changing environrnent are provided. The effectiveness of the system is shown in experiments.