Towards Fast High-Level Estimation of Inspection Drone Networks for Large-Scale Digital Twins

Large-scale digital twins are a subject of future developments since they require many resources for deployment and maintenance. Exemplary domain areas for such digital twins are countrywide road networks and cellular networks. Inspecting such systems is challenging because of the extensive geography. Drone inspection has become a common trend for gathering different sensor data in hard-to-reach areas and for repetitive, continuous inspection. The latest advances in this area concentrate on autonomous inspection. However, utilizing large-scale drone inspection networks stays out of the main focus for state-of-the-art research. This paper presents an extension for a digital twin of the road system framework. We focused on high-performance algorithms for the preliminary planning stage for inspection network stationary hub locations. The results stated in this paper show the possibility of a close-to-real-time preliminary analysis of a regional inspection network and a fast enough countrywide analysis. The application area of this extension is not limited to drone inspection. With improvements to some workflow steps, the extension can be adapted for other preliminary planning tasks.