Biochemical transport modeling, estimation and detection in realistic environments

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.