Phase I of READI involved characterizing threats in the environment, creating probabilistic models of risk assessment and course of action using Charles River’s probabilistic programming framework, Scruff™, and then creating visualizations to support decision-making for security personnel. Potentially disparate pieces of information, when viewed together in context, can lead to critical insights, McGeorge explains. By itself, an individual piece of information need not signify a threat, but when stitched together with others, it might. Risk assessments change accordingly, as do recommended courses of action.

A similar approach will likely apply to evaluation of natural disasters, while factoring in environmental data, and is expected to form the basis of the next phase of the READI project. Phase II will focus on a wider range of threats caused by natural disasters such as hurricanes, floods, and fires. Under a related NASA-funded effort called WIMPLE, Charles River has created a hybrid AI-based decision support tool for wildfire risk assessment and mitigation.

Updating risk assessments according to new and emerging threats, as READI does, helps security and emergency management teams respond faster and more efficiently. “There’s an opportunity to catch problems sooner than you might have otherwise,” McGeorge says.

Commercial applications could extend to use by emergency management organizations of municipalities and even for security management of large events.