Source detection algorithms for dynamic contaminants based on the analysis of a hydrodynamic limit

TL;DR

This paper introduces a novel algorithm for detecting contaminant sources using dynamic sensors, grounded in hydrodynamic limit analysis and probabilistic optimization, with demonstrated numerical effectiveness.

Contribution

It presents a new source detection algorithm based on hydrodynamic limit analysis and probabilistic optimization for dynamic sensor networks.

Findings

Algorithm effectively detects contaminant sources in simulations.

Hydrodynamic limit analysis informs the algorithm design.

Numerical results confirm the algorithm's efficiency.

Abstract

In this work we propose and numerically analyze an algorithm for detection of a contaminant source using a dynamic sensor network. The algorithm is motivated using a global probabilistic optimization problem and is based on the analysis of the hydrodynamic limit of a discrete time evolution equation on the lattice under a suitable scaling of time and space. Numerical results illustrating the effectiveness of the algorithm are presented.