Evolving Remote Sensing Applications as System-of-Systems

Abstract

There has been significant expansion in the functionality and differentiation of modern remote sensing applications due to the exponential growth in adoption of Unmanned Aerial Vehicles (UAVs). With recent advancements of new technologies such as Artificial Intelligence - Machine Learning (AI-ML) and Cloud Computing, many opportunities have emerged to significantly evolve UAV based remote sensing applications. This paper presents a novel approach to evolve remote sensing application as a System-of-Systems (SoS). Bringing in the SoS perspective provides additional insights into the dynamics of the interactions between the various constituent systems (e.g. swarm UAVs, Ground stations) and the impact on the overall remote sensing application. Systematically analyzing the relationships between the various Measures-of-Effectiveness (MOEs) of the SoS vis-a-vis the constituent systems, in tandem with the evolution of the MOEs, would enable optimal leverage of the recent technology advancements for remote sensing applications