Paper Info
Title
Biochemical transport modeling, estimation and detection in realistic environments
Abstract
Simulation, detection and estimation of the spread of a biochemical substance are key elements in environmental monitoring. Solving these problems are important for efficient decontamination purposes and prediction of the cloud evolution.We present a set of tools describing the measurements of an array of biochemical sensors through a physical dispersion model, which is amenable to statistical analysis. We first approximate the dispersion model of a contaminant in a realistic environment (for instance urban) through numerical simulations of reflected stochastic diffusions describing the microscopic transport phenomena due to wind and chemical diffusion using the Feynmann-Kac formula. Second, we propose a Bayesian framework based on a random field for localizing multiple dispersive sources with small amounts of measurements. Third, we present a sequential detector allowing on-line analysis and detecting whether a change has occurred, based on realistic numerical simulation. Numerical examples illustrate our results for a dispersion among buildings.
Year
DOI
Venue
2008
10.1109/ICASSP.2008.4518823
Las Vegas, NV
Keywords
Field
DocType
biosensors,chemical sensors,decontamination,diffusion,statistical analysis,feynmann-kac formula,biochemical sensors,biochemical transport,chemical diffusion,environmental monitoring,multiple dispersive sources,realistic environments,array signal processing,bayesian estimation,sequential detection,biochemical diffusion,sensors,inverse problems,homeland security,dispersion,modeling,chemicals,contamination,turbulence
Dispersion (optics),Random field,Simulation,Turbulence,Algorithm,Transport phenomena,Inverse problem,Engineering,Detector,Bayes estimator,Bayesian probability
Conference
ISSN
ISBN
Citations 
1520-6149 E-ISBN : 978-1-4244-1484-0
978-1-4244-1484-0
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Mathias Ortner17810.81
Nehorai, Arye21934309.00