Intelligent Automation, Inc. — Department of Defense SBIR Phase I: N211-025

Description

Future battlefield systems face unprecedented threats that require the adaptability to the emerging challenges. To achieve this purpose, military stakeholders need to consider several emerging technology advances that allows battlefield systems to rapidly respond to new enemy threats. Among these promising technologies are self-managing airborne networks, agile communications, cloud/edge computing architectures and app services. However, a careful assessment of the joint effect of these capabilities is still missing. Thus, there is a need to carefully assess the emerging capabilities and their joint impact on the mission effect chain outcomes. To address this critical need, Intelligent Automation Inc (IAI) proposes the design of SORT: a machine learning based analysis framework for tactical cloud/edge airborne battlefield systems. The key innovation of SORT is an intelligent data-driven system-level analysis framework that allows the assessment of multitude of design considerations of tactical cloud/edge airborne battlefield systems and the production of insights about the effect of the design parameters on the system performance, in particular the mission effect outcomes.