


Using iris recognition to improve airport security and travel experience
Today, airports around the world are tasked with ensuring the safety of their employees and passengers. In addition to providing error-free security, the service should be fast and airport employees should be courteous. Even before the Covid-19 pandemic began two years ago, when flights were filling up and demand outstripped service, airport managers recognized the need to plan for the future, improving traveler experience by upgrading infrastructure and developing innovative plans to speed up airports. of the airport check-in experience, providing benefits and reducing customer input.
The case of airports such as Hamad International Airport (HIA), Schiphol Airport and the Canadian Air Transport Safety Authority (CATSA) has answered the need for improved security, including the adoption of biometric technology. Private companies such as CLEAR are also venturing into biometric authentication solutions to provide faster and more secure ways to check in at airports or entertainment venues.
Admittedly, operating an airport is difficult; it must balance the needs for efficiency, customer service and safety. Iris technology is a solution that meets this need and evolves with the industry to help influence the future of air travel.
Meeting Today’s Aviation Demand
Demand for air travel has returned to pre-pandemic levels, leading to long lines and increased wait times at security checkpoints. To prevent missing flights, the TSA (Transportation Security Administration) currently recommends that travelers arrive at the airport two hours before domestic travel and three hours before international travel. This advice is the exact opposite of what travelers really want.
The International Air Transport Association (IATA) reported in its 2021 Global Passenger Survey that 85% of air travelers expect to spend less than 45 minutes at the airport with carry-on baggage only. Those traveling with checked luggage can expect to spend no more than an hour.
Amsterdam Airport Schiphol also operates its Privium program using iris recognition technology, which enables Dutch citizens and travelers to get through security in 15 seconds or less.
Such a clear disconnect between customer demand and reality only highlights the need to increase passenger throughput. Unfortunately, airport facilities management teams already face a host of challenges beyond just reassuring travelers.
Airport security requirements are unmatched in complexity and oversight. Facilities not only oversee passenger safety, but also manage employees and third-party workers. Therefore, the management team is tasked with maintaining all secure environments through accurate authentication and verification while providing a high level of customer satisfaction.
This duality of high security and high service creates a huge operational gap in the airport environment that requires innovative process re-engineering and comprehensive operational improvements to repair. Iris recognition technology provides an advanced contactless authentication solution for use at self-securing electronic gates, information kiosks, and immigration and border control lanes. This biometric solution allows passengers to speed through security checkpoints in less than 10 seconds, meeting the need for best-in-class security, fast throughput and a seamless travel experience.
Why Iris Recognition
Iris recognition provides a viable solution for air travelers and airport security professionals. It ensures fast throughput of security checkpoints by employing the most secure and accurate form of non-intrusive biometric authentication. The iris alone has 240 recognition points – far more than fingerprint and facial technology.
Additionally, each person’s irises are unique, resulting in fewer false positives and absolutely no opportunity for bias. Unlike ID cards and passports, unique iris patterns are not easily stolen, lost or damaged. This makes iris recognition technology highly reliable and ideal for accurately verifying and authenticating identities.
In airport operations, the unique capabilities of iris recognition have also been proven to improve security, speed and user satisfaction when used for personal identification. Complete registration and instruction may take less than 2 minutes. There was no invasive scanning while the subject stood one meter away from the scanner. Iris recognition uses camera-like technology to take a picture of the iris and uses a coding algorithm to create a digital template, forming a unique value that matches only one person. Once signed up, authenticating an individual takes less than 2 seconds and provides a completely contactless access control experience.
Making security checks faster, smoother and safer is a win-win for travelers and those responsible for airport operations. The same goes for people who need access to secure areas. This includes third-party contract workers who frequently use air facilities to transport goods and provide supplier services. The ability to closely monitor all persons entering secure areas is just as important as keeping the public out. Iris recognition can control access to these sensitive areas within airport operations and enable airline personnel and vendors to be easily identified and granted access to the appropriate areas.
The application of iris recognition technology in the airport environment, whether for customers or employees, can bring many benefits to airport operations. For example, self-service biometric kiosks at electronic gates eliminate the need for manual passport checks. Low-risk travelers can move quickly through security checkpoints, while managers can focus more attention on unknown travelers. Saved labor resources can now be reallocated across the airport to address additional operational or security processes. Additionally, by saving more time at security checks, passengers can spend more time at the airport’s services or hanging out, thereby improving their travel experience.
PROVEN SOLUTION
Millions of passengers use biometric-enabled immigration counter e-gates at Hamad International Airport in Doha, Qatar every year. ICAO praised the Hamad International Electronic Gate Program as a model system that can be adopted by other countries. To expand on this success, iris recognition technology found at immigration counters and electronic gates has been deployed to more than 500 border crossings in Qatar. The solutions will also be used to process the identities of approximately 3 million visitors ahead of the 2022 FIFA World Cup.
Except in Qatar, iris recognition is already being adopted globally to process trusted travelers simply, quickly and securely. CLEAR is a private company based in New York that uses iris authentication software and cameras embedded in kiosks to identify vetted travelers at more than 40 major U.S. airports. Amsterdam's Schiphol Airport also uses iris recognition technology to run its Privium program, which enables Dutch citizens and travelers to get through immigration and customs in 15 seconds or less. The same technology is extended to manage access to the airport’s three lounges, all of which are exclusive to members of the Privium program.
In 2004, the Canadian Air Transport Safety Authority (CATSA) deployed a unique iris recognition system for employee use only. Each CATSA employee's iris biometric is registered and stored on a smart card, which is used to gain access to secure areas. The iris recognition technology is integrated with existing physical access control systems installed at each of the 41 individual CATSA airports. An estimated 200,00 employees have already participated in the program, proving that biometrics can be used in aviation physical security beyond passenger-facing applications. By storing iris data on smart cards, CATSA resolves any privacy concerns and complies with the latest GDPR regulations.
Iris recognition technology provides a complete solution for accurate authentication for security and access control. The key to wider adoption is education about the convenience of the technology and more communication about current use. In IATA's 2021 Global Passenger Survey, 73% of travelers were willing to share their biometric data to improve airport processes, up from 46% in 2019.
Airline customers have proven that the convenience of digital solutions is attractive. Passengers can book flights, select seats, receive flight update notifications and download digital boarding passes through the airline app. It’s this ease of use that passengers want to see replace the time-consuming, repetitive security checks they go through on arrival. If consumers and security administrators stay up to date on the technology and its benefits, it is reasonable to predict mass adoption and opt-in for biometric programs. Massive educational marketing, visible signage and announcements of the deployment of biometric technology will certainly help.
The Airport of the Future
20th century air transportation infrastructure is already strained by the demands of 21st century airport operations and the impact of a waning global pandemic. In this volatile business environment, airports around the world face extraordinary challenges, including the inherent tension between improving operational efficiency, customer service and the overall travel experience while responding to a wide range of security threats.
Iris recognition has proven to be an effective and preferred authentication method to address these challenges in a 21st century world – where consumers now don’t like to wait, but also want their security promised. As the technology develops and product and deployment costs decline, iris recognition technology will become the preeminent biometric technology for airport security.
The above is the detailed content of Using iris recognition to improve airport security and travel experience. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP

Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application

To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text

Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year

Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
