Hardware-in-the-loop simulations of remote sensing disaster monitoring systems with real-time on-board computation

Real-time monitoring systems in remote sensing could enable a variety of new applications concerning emergency and disaster management. Coupling remote sensing imaging devices with hardware accelerators for artificial intelligence (AI) post-processing algorithms can pave the way for future constellations of small satellites offering services such as detection of wildfires, volcanoes eruptions, landslides, floods, etc. This paper presents MONSTER, a robotic facility hosted in the ARCA laboratory (ARCAlab) at the School of Aerospace Engineering in Rome. The facility was born as a simulator of lunar landing operations, but is currently being updated to perform hardware-in-the-loop simulation campaigns of many different scenarios including wildfires and volcanic eruption observation from space or airborne platforms. Having the possibility to perform translation and rotation maneuvers of the target observation platform, properly simulating the terrain, and performing the AI-aided computation on hardware accelerators such as graphics processing units (GPUs), visual processing units (VPUs), and field programmable gate arrays (FPGAs), the MONSTER facility could be used to efficiently simulate new remote sensing paradigms for disaster monitoring through on-the-edge artificial intelligence.