Defending Large-Scale Critical Infrastructures Using a Swarm of Drones

The use of fleets of drones for infrastructure monitoring has seen significant rise in the last decade, with the growing availability of increasingly cheaper and more reliable platforms. This trend can be observed in a variety of civilian domains such as road safety, homeland security and environmental control. In addition, the reliance on drones for targets detection, traction and interception is becoming a key element in the operational paradigms of modern militaries - both under symmetric conflicts scenarios as well as asymmetric ones. Whereas different drone-based applications may have different operational requirements, they all share a common desire - to maximize the overall impact of a given drones fleet, or alternatively, to minimize the overall cost required to successfully accomplish a given assignment. Current mainstream drone operative doctrines relies mainly on human operators for the design and constant adaptation of the drones flying routes, often allocating a professional operator for each individual drone (with some exceptions of a handful of new systems that are comprised of a small number of self-organizing swarms, manually guided by a human operator). In this work we propose a novel approach for the optimization of large-scale swarms of reconnaissance and monitoring drones - capable of producing on-demand optimal strategies for any pre-defined search scenario. Given a threat and its estimated potential damages, as well as types of monitoring drones available and their comparative performance, our proposed method generates an analytically provable strategy and determines the optimal number and type of drones to be deployed in order to cost-efficiently monitor a pre-defined region for mobile targets that use a known roads network.