Optimal deployment of unmanned aerial vehicles for border surveillance

Abstract

Border surveillance is an important concern for most nations wanting to detect and intercept intruders that are trying to trespass a border. These intruders can include terrorists, drug traffickers, smugglers, illegal immigrants, and others who represent a threat to national interests. Unmanned aerial vehicles (UAVs) allow for modernization and improvement of border surveillance. There are a number of advantages to using UAVs. Many UAVs can be controlled by a single operator, which reduces personnel costs; they are very fast and can patrol large regions; and they have wider regions of visibility than conventional surveillance methods, which increases the probability of detecting intruders. This thesis formulates mathematical models designed to find the best way to utilize a given fleet of UAVs by deciding their routes, altitudes, and speeds in order to maximize the probability of detecting intruders trying to trespass a given border. These models will enable decision makers to effectively acquire and employ a UAV fleet for border surveillance.