An Integrated Testbed for Supporting Sustained Military Installation Decision-Making and Modernization

Abstract

The vision of the Army Installations Strategy (AIS) and the Installations of the Future (IotF) program is to enhance mission effectiveness and resilience in a prudent, efficient, and forward-thinking manner, including Army installations and contingency bases, energy, and environmental programs. Modernization of the nation’s installation portfolio has many challenges. One challenge is due to the lack of a framework for acquiring and transmitting data to and from government networks and systems for implementing modernization efforts. This research effort supports AIS and IotF by contributing to the modernization of installation decision-making processes by providing a data-driven platform for applying complex computational analytics and high-performance computing assets within the Virtual Testbed for Installations Mission Effectiveness (VTIME) integrated platform. This approach supports installation decision-makers for making holistic tactical and operational decisions. Current decision processes are predominantly manual in nature, require extensive human interactions, and lack relevant data. This research integrates various analytical methods, such as machine learning (ML) in conjunction with real-time data, to power a decision dashboard that can more effectively communicate the impact of risks to an installation. The desired outcome will create a sustainable and translational data-driven decision framework that will inform leadership for the installation operations decision process. This paper explores the ML analytics applied to historical data that provide insight to support the modernization of the weather-impacted installation operations decision flow process.