Last year, Buzzfeed broke the story that US law enforcement agencies were using small aircraft to observe points of interest in US cities, thanks to analysis of public flight-records data. With the data journalism team no doubt realizing that the Flightradar24 data set hosted many more stories of public interest, the challenge lay in separating routine, day-to-day aircraft traffic from the more unusual, covert activities.
So they trained an artificial intelligence model to identify unusual flight paths in the data. The model, implemented in the R programming language, applies a random forest algorithm to identify flight patterns similar to those of covert aircraft identified in their earlier "Spies in the Skies" story. When that model was applied to the almost 20,000 flights in the FlightRadar24 dataset, about 69 planes were flagged as possible surveillance aircraft. Several of those were false positives, but further journalistic inquiry into the provenance of the registrations led to several interesting stories.
Using this model, Buzzfeed news identified several surveillance aircraft in action during a four-month period in late 2015. These included a spy plane operated by US Marshals to hunt drug cartels in Mexico; aircraft covertly registered to US Customs and Border Protection patrolling the US-Mexico border; and a US Navy contractor operating planes circling several points over land in the San Francisco Bay Area — ostensibly for harbor porpoise research.
You can learn more about the stories Buzzfeed News uncovered in the flight data here, and for details on the implementation of the AI model in R, follow the link below.
Github (Buzzfeed): BuzzFeed News Trained A Computer To Search For Hidden Spy Planes. This Is What We Found.