The monitoring of a diffuse process, such as the propagation of a toxic gas in an area, using the partial differential equation (PED) model via autonomous wireless sensor networks is studied in this research. Sensor nodes update the base station with their estimates of PDE model parameters rather than raw sensor measurements. Then, the base station can reconstruct the phenomenon through model parameters and initial and boundary conditions. In-network processing techniques to estimate the PDE coefficients are presented. A scheme is presented to provide a hybrid combination of decision and data fusion to find a proper tradeoff between estimate accuracy and energy efficiency. Besides, several open issues in this research context, such as identifiability of parameters, monitoring of time varying boundary conditions and unknown sources, are discussed.
This work studies the problem of node clustering for wireless sensor networks. In this context, clustering is intended as the process of electing leader nodes and partitioning the remaining nodes among the leaders. Clustering is needed in any tasks and applications for sensor networks that require some form of locally centralized
processing. This work proposes a graphical model that represents node clustering as a graph cutting problem. This model is considered in different application contexts. In order to deal with a reduced number vertices and edges, a semi-dynamic clustering strategy is proposed: i.e. new clusters are formed over an a priori defined sensor
partitions. Existing clusters are split into subclusters A cluster or a portion of it is just viewed as a macronode. Finally an heuristic implementation of the above ideas is applied to a multiple target tracking scenario in particular to the tasks of multiple target counting and localization.
An automatic web content classification system is proposed in this research for web information filtering. A sample group of web contents are first collected via commercial search engines. Then, they are classified into different subject group and more related web pages can be searched for further analysis. It can free from the troublesome and routine process that are performed by human beings in most search engines. And the clustered information can be updated at any specified time automatically. Preliminary experimental results are used to demonstrate the effectiveness of the performance of the proposed system.