How AI-based biometric algorithms are reshaping the travel experience
AI – what is it?
AI refers to machine intelligence—the ability of computers and systems to emulate human thinking. It encompasses learning, planning, problem-solving, and decision-making. AI systems are designed to mimic cognitive functions associated with human minds, enabling them to analyse data, adapt to new situations, and improve over time without explicit programming for every scenario.
In order to reach any conclusion, machines use algorithms. These algorithms have frameworks that make it possible to process data to meet a specific need and learn from it. But this can only be achieved through the partnership between artificial and human intelligence. The true source of intelligence is human rather than artificial. Although it is nearly impossible to process the amount of data and to draw conclusions from there as fast as machines do, it’s the human intelligence that creates the step-by-step guide for an algorithm to know what to do and learn from it. Without this knowledge, it wouldn’t be an AI. Artificial intelligence is not independent of human touch, it’s a continuation of human intelligence.
The technology
Behind all Vision-Box’s solutions, there’s an AI-based facial recognition engine, that leverages state-of-the-art deep learning technologies and computer vision algorithms for face processing and matching.
Deep learning is a subset of AI inspired by the structure and function of the human brain's neural networks. Through layers of interconnected nodes, known as neurons, deep learning models can learn to identify intricate patterns from vast amounts of data. This capability is particularly well-suited for tasks that involve complex decision-making and pattern recognition, making it ideal for biometric applications.
Biometrics, on the other hand, refers to the measurement and statistical analysis of biological data, to recognise individuals and identities. This can include various physiological and behavioural characteristics unique to individuals, such as fingerprints, iris patterns, facial features, voiceprints, and even gait. By leveraging deep learning techniques, biometric algorithms can analyse and interpret these characteristics with remarkable precision, enabling robust authentication and identification systems.#
One of the most compelling areas where AI in deep learning trained algorithms shines is in the domain of image and speech recognition. Convolutional neural networks (CNNs) are a type of deep neural networks that was primarily designed to process and analyse visual data, therefore playing a pivotal role in this domain by creating hierarchical representations of features extracted from input images. This enables a wide range of tasks, including object recognition, classification, segmentation, and more.
Biometric algorithms and the travel industry
Biometric algorithms, powered by deep learning techniques, offer a paradigm shift in identity verification and authentication, particularly in the context of travel and border control. Instead of relying on credentials like an identity card or other type of identification, biometrics enables travellers to use their physiological traits as their passport. By analysing biometric unique features, such as fingerprints and face, these algorithms enable seamless and secure identification of travellers. Some key applications include efficient border control, secure passenger boarding, customised travel experiences, and enhanced security measures.
Biometric systems equipped with deep learning algorithms streamline the border control process, allowing authorities to verify travellers' identities quickly and accurately. These systems enhance security and operational efficiency at border crossings by eliminating the need for manual document checks and reducing queue times. On the other hand, travel operators such as airlines and airports are increasingly adopting biometric boarding solutions powered by deep learning algorithms. By linking travellers' biometric data to their boarding passes, these systems enable touchless and secure boarding processes, reducing boarding times and enhancing security measures.
Biometric authentication facilitates personalised travel experiences, allowing travellers to access exclusive services and amenities seamlessly. From expedited security clearance to personalised recommendations and loyalty program perks, biometric algorithms enhance the overall travel experience for passengers. Deep learning trained biometric algorithms offer enhanced security measures by accurately identifying individuals based on their unique biometric signatures. This helps prevent identity theft, fraudulent activities, and unauthorised access to sensitive areas within airports, train stations, and other transportation hubs.
Nonetheless, as biometric technology becomes more pervasive, having privacy at the base of any solution is key. Vision-Box is Privacy-by-Design certified, addressing these concerns with careful consideration of regulatory frameworks, transparent practices, and responsible deployment of biometric systems.
Conclusion
Artificial intelligence is reshaping the future of travel while connecting the world, offering travellers unprecedented convenience, security, and personalisation. From personalised recommendations to seamless authentication and border control, AI is revolutionising every aspect of the travel experience. Moreover, as biometric technology continues to advance, it promises to unlock even more seamless and secure travel experiences, paving the way for a future where journeys are not just about reaching destinations but about the transformative experiences along the way. As we embrace these technological advancements, it's essential to prioritise privacy, security, and ethical considerations, ensuring that AIpowered travel processes benefit all stakeholders while respecting individual rights and freedoms. With the help of AI, the future of travel is boundless, offering endless possibilities for exploration, discovery, and connection.
Identity management plays a central role in converting complex traveller digital data processing into a truly contactless seamless travel experience. The Vision-Box Facial Recognition Engine is delivered as part of Vision-Box’s Seamless Journey Platform®, a digital identity management platform for connecting multiple stakeholders around the traveller journey, enhancing security, customer experience and operational efficiency.
Heather Cover-Kus
Heather is Head of Central Government Programme at techUK, working to represent the supplier community of tech products and services to Central Government.
Ellie Huckle
Ellie joined techUK in March 2018 as a Programme Assistant to the Public Sector team and now works as a Programme Manager for the Central Government Programme.
Annie Collings
Annie joined techUK as the Programme Manager for Cyber Security and Central Government in September 2023. In this role, she supports the Cyber Security SME Forum, engaging regularly with key government and industry stakeholders to advance the growth and development of SMEs in the cyber sector.
Austin Earl
Austin joined techUK’s Central Government team in March 2024 to launch a workstream within Education and EdTech.
Ella Gago-Brookes
Ella joined techUK in November 2023 as a Markets Team Assistant, supporting the Justice and Emergency Services, Central Government and Financial Services Programmes.
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