An Adaptive Model of Hierarchical Sensor Uncertainty Coordination Based on MAS and RST

In this paper, focusing on the idea of establishing a more coherent and robust sensor uncertainty management framework, we first suggest that different levels of sensor data uncertainties need to be evaluated and organized into a hierarchy. In particular, in consideration of the potential of distributed coordination among sensor nodes due to the inherent association between wireless sensor networks and multi-agent systems, also in a rough set technique sense under imprecision and partial truth, we further present an adaptive model of hierarchical sensor uncertainty coordination, which includes local data fusion, global and rational decision, along with conflict resolution. Experimental results of an example case study of our proposed approach demonstrate the practical application to the certainty improvement of noisy sensor readings.