Collaborating Authors


Delta to begin using facial recognition cameras at an LAX

Daily Mail - Science & tech

Delta Air Lines will implement facial recognition technology at Los Angeles International Airport from Friday, with cameras identifying passengers at a boarding gate with more to be installed after. The move has been met with controversy however, as groups such as Greenpeace call for a federal banning of the technology by law enforcement agencies. Critics say the technology could be used to violate privacy and date, as well as pointing to issues with accuracy for non-white male subjects. A spokeswoman for the coalition of groups, which also includes MoveOn and the Electronic Privacy Information Center, said the groups also oppose the use of the technology by airlines. 'There is no real oversight for how a private corporation can use our biometric information once they've collected it,' said Evan Greer, deputy director of Fight for the Future.

If Chicago O'Hare is on your flight plan, you could be in trouble

Los Angeles Times

Chicago O'Hare International Airport had the highest number of flight disruptions Wednesday morning as a massive winter storm made its way across the U.S. It will bring snow, rain and an "icy mix" to parts of the Midwest and East on Wednesday evening. As of Wednesday morning, more than 2,000 flights in the Midwest and Northeast had been canceled, and another 3,000 delayed because of the storm, according to FlightAware. The flight-tracking website showed Chicago O'Hare as the worst place for disruptions between 7 and 11 a.m. CST, with 51 flights canceled and 163 delayed. Baltimore-Washington, Reagan National and Dulles airports in the Washington area also showed significant flight problems, with a combined total of 84 flights canceled and 51 delayed as of Wednesday morning.

TSA using robots?

FOX News

The Transportation Security Administration (TSA) and American Airlines say they have the solution to increasingly long wait times at U.S. airports--automation. On Tuesday, TSA announced its new partnership with the legacy carrier to speed up the screening process through several initiatives with new technology, including more CT scanners and automated screening lanes. The automated security lanes, which are currently being tested at Hartsfield–Jackson International Airport in Atlanta, could reduce the time travelers spend waiting by as much as 30 percent, says the agency. TSA spokesman Michael McCarthy told the Chicago Tribune that the technology used to screen carry-on luggage has remained relatively stagnant over the past 15 years, save for software upgrades. The automation process should "shave a few seconds from every step"--seconds that add up when screening thousands of passengers. The automated lanes, known as "Smart Lanes" at Hartsfield–Jackson, take up more space than traditional security lines but move luggage through faster.

Propagation of Delays in the National Airspace System Artificial Intelligence

The National Airspace System (NAS) is a large and complex system with thousands of interrelated components: administration, control centers, airports, airlines, aircraft, passengers, etc. The complexity of the NAS creates many difficulties in management and control. One of the most pressing problems is flight delay. Delay creates high cost to airlines, complaints from passengers, and difficulties for airport operations. As demand on the system increases, the delay problem becomes more and more prominent. For this reason, it is essential for the Federal Aviation Administration to understand the causes of delay and to find ways to reduce delay. Major contributing factors to delay are congestion at the origin airport, weather, increasing demand, and air traffic management (ATM) decisions such as the Ground Delay Programs (GDP). Delay is an inherently stochastic phenomenon. Even if all known causal factors could be accounted for, macro-level national airspace system (NAS) delays could not be predicted with certainty from micro-level aircraft information. This paper presents a stochastic model that uses Bayesian Networks (BNs) to model the relationships among different components of aircraft delay and the causal factors that affect delays. A case study on delays of departure flights from Chicago O'Hare international airport (ORD) to Hartsfield-Jackson Atlanta International Airport (ATL) reveals how local and system level environmental and human-caused factors combine to affect components of delay, and how these components contribute to the final arrival delay at the destination airport.