Monitoring of diffusion processes with PDE models in wireless sensor networks | Zendy

Lorenzo Rossi | Zendy; Bhaskar Krishnamachari | Zendy; C.C. Jay Kuo | Zendy

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Monitoring of diffusion processes with PDE models in wireless sensor networks

Author(s) -

Lorenzo Rossi,

Bhaskar Krishnamachari,

C.C. Jay Kuo

Publication year - 2004

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.542719

Subject(s) - wireless sensor network , context (archaeology) , identifiability , partial differential equation , base station , computer science , boundary (topology) , sensor fusion , diffusion , real time computing , boundary value problem , process (computing) , raw data , wireless , mathematical optimization , data mining , algorithm , mathematics , telecommunications , artificial intelligence , computer network , machine learning , mathematical analysis , paleontology , physics , biology , operating system , thermodynamics , programming language

The monitoring of a diuse process, such as the propagation of a toxic gas in an area, using the partial dierential 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 coecients are presented. A scheme is presented to provide a hybrid combination of decision and data fusion to find a proper tradeo between estimate accuracy and energy eciency. Besides, several open issues in this research context, such as identifiability of parameters, monitoring of time varying boundary conditions and unknown sources, are discussed.

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