With airports and airlines struggling to keep up with passenger demand and staffing issues, air travel is challenging in a thousand different ways. What hasn’t changed, in this sea of change, is the importance of safety. The technology used for safety measures and screening, however, is undergoing some exciting developments.

AI has invented a new software that can detect threats and enhance airport security to assure safer travel. This article will discuss how automated threat detection technologies increase security at airports.

What Is Automated Threat Recognition?

Automated Threat Recognition (ATR) software examines physical items or human body scan data to detect areas where contraband can be kept hidden. These identified sections are flagged on a standardized display to inform the security officer which areas to perform a manual search on.

Scanners perform automated threat recognition on images to detect threat objects. Enhanced automated threat recognition will improve the detection of threatening items. Advanced automated target recognition algorithms will help enhanced 3D Computed Tomography (CT) Scanners—CT-based object detection equipment—by enhancing object recognition techniques, similar to CT scans that are performed at the hospital on brains!

The Challenges Of Airport Authorities and Government

Created in the wake of the 9/11 terrorist attack in the US, the Transportation Security Administration (TSA) is tasked with protecting United States air travel. They hire human inspectors to check passengers and baggage for prohibited items and threats using scanners and x-ray images. This task sometimes becomes difficult, particularly when you consider that often the machines used don’t communicate with each other. There is an acute need for improvement. In tests conducted by Homeland Security in 2015 (where agents attempted to pass through security with contraband) the TSA screening failed 95% of the time.

The Open Threat Assessment Platform (OTAP) project is working to change stats like this. Researchers from Stratovan and Sandia Nationwide Laboratories are taking an important role in airport safety innovation. They are working from the position that some existing technology and processes are too rigid and needlessly time-consuming. For instance, having everyone take off their shoes or enforcing the current restrictions on aerosols, liquids and gels could possibly be approached differently.

Travelers who are now used to today’s standards may be surprised to know that prior to 9/11, things were very different for those departing US airports:

• Blades up to 4 inches were permitted on the plane.
• Baseball bats, box cutters, darts, and scissors were also allowed on the plane.
• Family members were able to go through security to the departing gate to say goodbye.
• Passengers could keep shoes on when going through security.
• Passengers could carry liquids onto the plane.
• The only security screening was a metal detector.
• No ID was required.
• Passengers would only need to arrive 30 minutes before their flight to ensure they would make their flight.

Over the last two decades, airports across many countries have worked on their security enhancement to prevent emerging threats. They are trying hard to make the journey from entrance to exit gate as seamless as possible.

For many governments and aviation centers, the improvement of artificial intelligence is the best solution. The UK Government has already invested £1.8m into the development of new AI security systems, a full-scale roll out of new biometric services, and are working to reduce wait times across some of their busiest airports.

The US Transportation Security Administration has implemented new CT scanners, which utilize AI to help target threats, at Los Angeles International Airport, John F. Kennedy and Phoenix airports.

AI Software for Security Systems

AI is implemented across the entire aviation spectrum, from self-service check-in robots to facial recognition checks at customs. On the other side, recent research applying deep learning techniques to computer-aided security screening to assist operators showed encouraging results.

AI systems work on various datasets. For airport security, technologists use machine learning to analyze data and identify threats faster than humans. Objects that previously needed to be scanned separately, can be kept in passenger luggage as they pass through security checkpoints.

The OTAP project described above was developed with many aviation security industry partners including algorithm developers, X-ray vendors and software specialists to build the Open Platform Software Library (OPSL).

Similarly, Pacific Northwest National Laboratory developed a High-Definition Passenger Imaging System, which can scan a body. In 2017, Sandia joined forces with PNNL to add the scanner with OPSL to make an advanced full-body machine that can more accurately detect threats.

The team is now using automated threat recognition software to advance sensors—CT and AIT systems—by testing with bags, toiletries, laptops, and simulated explosives, to show the device’s accuracy.

AI-Powered Baggage Screening

Airport Authority Of India (AAI) has chosen eight airports to test the capabilities of Artificial Intelligence in baggage screening. Pune airport is one of them, which implemented the ‘”Baggage AI” system. The AI-powered device strengthens the security efforts at the airport.

Baggage AI is an artificial intelligence-based model which is the threat detection system for security x-ray machines. This AI software can automatically identify various objects and other threats from the x-ray images created during the screening of baggage and alert operatives.

Use Of Biometrics In Airport Security

One remarkable invention in AI is biometrics. Major airports have decided to use biometric ID management over the next couple of years. The primary purpose of biometrics is facial recognition, which is already operational to scan passengers as they pass through customs at a number of major airports.

Passengers can use facial recognition scanners at self-service kiosks, TSA checkpoints, or boarding gates. Fingerprinting, facial recognition, and retinal scans can become essential verification methods for security checking at airports.

Furthermore, tests are ongoing in behavioral biometrics. Researchers of the UK’s University of Manchester recently developed an AI system to measure people’s walking patterns when they step on a pressure pad.

Conclusion

Past failures and present-day threats have created an urgent need for these advanced AI-based technologies in airport security. Technology that reduces passenger friction during the hustle and bustle of travel, not having to take belts off, and keeping your shoes on has got to be a positive step for air travelers. AI not only can identify known threats but also detects unknown threats. AI is an integral part of cybersecurity, including its machine learning model. As automated threat recognition systems through AI advance over time, terrorist attacks could be predicted and controlled. More safety in the airports assures a peaceful journey for passengers.