This paper aims to suggest a multi modal biometric way as a solution to no touch preferences of the travellers adapting them to a self service model accelerating deployment. In the existing situation of Covid-19 pandemic, airport authorities are compelled to estimate presently available techniques for airport passenger experience and incorporate changes according to the prevailing conditions. This biometric modelling will definitely be a break through development in aviation field and airport management. Many of the airports have already implemented new health and safety measures to protect their employees and passengers, enhanced cleaning schedules, providing personal protective equipments (PPE) for all airport staffs and also health screening of employees and passengers.
There are several orthodoxies or blind spots prevailing among individuals and institutions which prevent them from accepting changes and adjusting to new and better ways of working. But actually little bit of fluctuations from these existing orthodoxies can pave way for drastic improvements. Covid-19 has become one such situation which have forced many people to think out of the box. These new needs of behavioural changes have enabled the airports to elevate and adapt themselves to address the increased awareness of passengers and airport employees post Covid-19.The strategies which were planned for long term and were valid some days before are no longer applicable forcing stakeholders and airport authorities to consider urgent changes.
The main challenge before the airports is to in still confidence in their customers that they can spend time safely and comfortably in airports. By doing different studies, the common five orthodoxies in the airport passenger experience challenged by Covid-19 are (i) Passenger Processing (ii) Self Service (iii) Biometric Enablement (iv) Employee Wellbeing (v) Flexible Service Delivery.
Earlier customers were largely satisfied by sped and efficiency. But today people are concerned about the possible time spent at chokepoints throughout the airport. Now there is an opportunity to improve customer satisfaction by enhancing technology based services to ease the passenger concerns by queue measurement to display wait times, tray return systems and use of biometrics with services like CLEAR for analysing the security threats as well. Other analytical solutions such as people tracking and terminal modelling enabled reduction of chokepoints and improves efficiency. All public places especially airports are probable zones of corona virus transmission. Every other passenger in the airport can be a potential carrier. Health screening of passengers have become a new challenge and the responsibility of which is now on the concerned airlines.
The main aim of the proposed study is to develop a transition model of the currently existing self service technologies in airport to no touch techniques thereby reducing the physical touch points prevailing in the airports.
For the realisation of the no touch techniques in airports a multi modal biometric analysis is suggested through this study. Biometric systems have a common architecture which consists of four main elements as shown in figure below.
In this work, we can make use of multi modal biometrics along with the fusion techniques. ECG, fingerprint and face biometric traits are selected for this purpose. By selecting ECG as a biometric tool, proofs of existence in real time conditions are less prone to spoofing. When face and fingerprint data are clubbed with ECG, a comparatively less obtrusive biometric is obtained. Fusion of ECG signal with fingerprint-face biometrics will lead to the development of reliable credentials of an individual. Therefore with the fusion of the said parameters the authentication performance and accuracy of the entire system gets enhanced.
ECG gives the details regarding the electrical actions of the cardiovascular muscles from the relative constrictions and relaxations of heart muscles. There are numerous studies on ECG data’s and each of them proved that it will be unique for a particular individual. The work also involves the breaking down of photographs of human faces. The advantage of breaking down of face picture is that each part i.e nose, eyes or morphology can be closely examined utilising the official data available. Fingerprint collection is one of the standout data’s that help in biometric modelling. Fingerprints can be procured by ultrasonic and optic sensors which will measure the valleys, edges, depressions and islands in a unique finger impression. Therefore a combination of ECG, face and fingerprinting can be done to develop an enhanced and efficient system of multi modal biometric. In addition to this feature extraction approach and cryptography is used to provide higher security.
By designing a proper multi modal biometric framework the performance of airports can be enhanced to above par level winning back the confidence of the regular users during Covid-19 and after as well. In the medium and long term, airports may even consider the re-evaluation of existing framework and add features according to the need of the time. This study will definitely help to identify possible retrofit opportunities, development of robust pandemic playbooks, accelerate implementation of biometric capabilities and enhancement and augmentation of operational modelling and simulation.
Simon Dixon et.al. How Covid-19 is challenging orthodoxies in airport customer service
Raju, A., & Udayashankara, V. (2018). A survey on unimodal, multimodal biometrics and its fusion techniques. International Journal of Engineering & Technology, 7(4.36), 689.
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