Monitoring of Diffusion Processes with PDE Models in Wireless Sensor Networks

摘要

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.