A comprehensive review of plume source detection using unmanned vehicles for environmental sensing

Abstract

Local meteorological conditions including wind speed and turbulence significantly influence the dispersion of pollutant plumes, introducing severe difficulties in predicting its trajectory, potential evacuation sites, and ultimately containment efforts. Ongoing developments in estimating rapid contaminant dispersion include the combined use of local meteorological data along with plume-source localization and identification via autonomous data-driven mobile-sensing robotic/vehicular platforms. With a vast number of available environmental-sensing mobile platforms, contaminant dispersion scenarios, and source-finding algorithms, selection of the ideal configuration for autonomous source localization involves a great deal of opportunity alongside uncertainty. This paper aims to review the significant developments of unmanned ground-based mobile sensing network configurations and autonomous data acquisition strategies commonly used for the task of gaseous plume source localization.

Keywords: Atmospheric dispersion modeling applications; Autonomous plume source detection algorithms; Mobile environmental sensing networks; Source term estimation; Unmanned ground vehicles.