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Predictive analysis — a tool that can be used to figure out the best way to get through an airport quicker, or how to keep you safe driving across bridges and through tunnels, or how to ascertain the true impact of a natural disaster —, serves as the backbone for many of S&T-developed technologies. One such predictive tool, is modeling. A model is an analytical, simplified representation of reality. It allows scientists and engineers to mathematically represent an area and insert variables to foreshadow certain outcomes, akin to the movie Minority Report. For the U.S. Customs and Border Protection’s Air and Marine Operations Center (AMOC), one of the biggest challenges is quantifying the effectiveness of long-distance radars in detecting, identifying, and classifying aircraft that cross our borders. AMOC monitors all non-commercial traffic in the U.S. and the volume of this effort affects the speed in which they can alert law enforcement to investigate certain aircraft. To fix the problem, AMOC reached out to S&T’s Operations & Requirements Analysis (ORA) Office for modeling expertise.
The partnership gave birth to the value-focused model (VFM). This VFM is a simulation that allowed both groups to evaluate AMOC’s contributions to U.S. air domain awareness and security.
“The reason we partnered with AMOC was to help better articulate their role in security,” said program manager Geoffrey Berlin. “They can use this modeling to improve their decision-making and to help them be more transparent to stakeholders.”
VFM captures the essence of the real-world, but allows for enough freedom to test different variables, like incorporating a new radar system or hiring more detection enforcement officers to monitor radar screens.
“As the Federal Aviation Agency (FAA) moves to a system that revolves around GPS to track flights rather than radars on the ground that track and ensure separation, it can have an adverse effect on AMOC’s ability to track those non-commercial flights,” said Senior System Analyst Arch Turner. “Anything that affects AMOC affects our security, so we felt compelled to help them in this endeavor to not only prove their value, but increase their value.”
Through modeling, ORA was able to show that without some of the capabilities AMOC provides, it becomes easier for aircraft to fly undetected at low altitudes along the southwestern U.S. border. The model provides a quantitative assessment of every mile along that border and illustrate how effective radar is and what would happen if it were no longer active. Without modeling, it makes it very difficult to calculate and understand vulnerabilities and more importantly, to visualize them.
“The models allow you to see it in a geospatial display,” said Turner. “Sort of a ‘God’s eye’ view.”
According to Berlin, this type of analysis also helps AMOC coordinate with law enforcement to determine threat levels and intercept an aircraft, either in mid-air or when it lands. The ORA team established a set of predictive analysis guidelines that examine several characteristics, such as time of day, altitude, flight trajectory, etc., which helps state, local, and tribal law enforcement officials safely prepare for a hostile situation and be safe. But on the other hand, it also helps them know when they’re going into a situation where a plane flying along the border has the equivalent of a busted tail light, which isn’t a big deal in the large scope of aviation security.
“We think this predictive capability has a lot of applications for homeland security, which we’re going to continue to explore,” said Turner.
There are patterns that the human eye may not notice but data does. Through the use of past, present, and future data, Berlin’s team is able to bring border patrol one step closer into a world only imagined in science fiction.