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Automated threat recognition technology and airport security

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Air travel is challenged in a thousand different ways, as airports and airlines struggle to keep up with passenger demand and staffing issues. What has not changed in this sea of ​​change is the importance of safety. However, the techniques used for safety measures and screening are undergoing some exciting development.

AI has invented new software that can detect threats, enhance airport security and ensure safer travel. This article describes how automated threat detection technology can improve airport security.

What is automatic threat recognition?

Automatic Threat Recognition (ATR) software examines scan data of physical items or human bodies to detect areas where smuggled goods can be hidden. These identified sections are flagged with a standardized display to inform security personnel of the area in which to perform a manual search.

The scanner performs automatic threat recognition on the image to detect threat objects. Enhanced automatic threat recognition improves detection of threatening items.Altitude Automatic goal recognition Algorithm helps eEnhanced 3D Computer Tomography (CT) Scanner— CT-based object detector — by strengthening object recognition technology It’s similar to a CT scan done on the brain in a hospital!

Airport authorities and government challenges

Created following the 9/11 terrorist attacks in the United States tThe Transportation Security Administration (TSA) is responsible for protecting US air travel. They hire human inspectors to use scanners and x-ray images to check passengers and baggage for prohibited items and threats. This can be difficult, especially given that the machines you use often do not communicate with each other. There is an urgent need for improvement.In the tests conducted by Homeland Security in 2015 The TSA screening has a 95% chance of failing (if the agent attempts to pass security using the contraband).

The Open Threat Assessment Platform (OTAP) project is working to change these statistics. With Stratovan Sandia National Laboratories taking it An important role in airport safety innovation. They work from the standpoint that some existing techniques and processes are too rigid and unnecessarily time consuming. For example, if you want everyone to take off their shoes or apply current restrictions to aerosols, liquids, and gels, you might approach them in a different way.

Travelers who are now accustomed to today’s standards may be surprised to find out before 9/11. Things were very different When departing from a US airport:

  • The plane was allowed blades up to 4 inches.
  • Baseball bats, box cutters, darts, and scissors were also able to fly.
  • The family was able to pass security to the departure gate to say goodbye.
  • Passengers can continue to wear shoes as they pass security.
  • Passengers can carry liquids on the plane.
  • The only security screening was a metal detector.
  • I didn’t need an ID.
  • Passengers only need to arrive 30 minutes before the flight to ensure the flight.

Over the last two decades, airports in many countries have been working to increase security to prevent new threats. They are working hard to make the journey from the entrance to the exit gate as seamless as possible.

For many governments and aviation centers, improving artificial intelligence is the best solution. The UK government has already invested £ 1.8 million in developing a new AI security system. Full-scale development of new biometric authentication service, And we are working to reduce waiting times at some of the busiest airports.

The Transportation Security Administration has implemented new CT scanners at Los Angeles International Airport, John F. Kennedy Airport, and Phoenix Airport that use AI to target threats.

AI software for security systems

AI is implemented throughout the aviation sector, from self-service check-in robots to facial recognition checks at customs. Meanwhile, recent studies applying deep learning techniques to computer-aided security screening to assist operators have shown promising results.

AI systems work with different datasets. When it comes to airport security, technicians use machine learning to analyze data and identify threats faster than humans. Objects that previously had to be scanned individually can be left in the passenger’s luggage as they pass security checkpoints.

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

Similarly, the Pacific Northwest National Laboratory has developed a high-resolution passenger imaging system that can scan the body. In 2017, Sandia worked with PNNL to add a scanner with OPSL to create an advanced full-body machine that can detect threats more accurately.

The team is now using automated threat recognition software to evolve sensors (CT and AIT systems) to improve device accuracy by testing on bags, toiletries, laptops, and simulated explosives. is showing.

Baggage screening using AI

The Airports Authority of India (AAI) has selected eight airports to test the function of artificial intelligence in baggage inspection. Pune Airport is one of them, “Baggage AI” system. AI-powered devices enhance airport security efforts.

Baggage AI is an artificial intelligence-based model that is a threat detection system for security X-ray equipment. The AI ​​software automatically identifies various objects and other threats from X-ray images created during baggage screening and alerts operatives.

Use of biometrics in airport security

One of AI’s notable inventions is biometrics. Major airports have decided to use biometric identity management over the next few years. The main purpose of biometrics is face recognition. This is already working to scan passengers passing through customs at many major airports.

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

In addition, behavioral biometrics testing is underway. Researchers at the University of Manchester in the United Kingdom have recently developed an AI system that measures gait patterns when people step on pressure pads.

Conclusion

Due to past failures and current threats, these advanced AI-based technologies in airport security are in urgent need. The technique of reducing passenger friction in the hustle and bustle of travel, not having to remove the belt and keeping the shoes on must be a positive step for air travelers. AI can not only identify known threats, but also detect unknown threats. AI is an integral part of cyber security, including machine learning models. As AI-powered automated threat recognition systems evolve over time, they will be able to predict and control terrorist attacks. The increased safety of the airport allows passengers to travel peacefully.

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