How to Move Large Groups of Passengers through Airport Terminals
Across the world, airports' limited capacity is already strained with the growing number of travelers. Amidst premium spaces and passengers' safety vital, operators are forced to employ intelligent capacity forecasting and planning to satisfy both sides of the equation.
Currently, airports struggle to cope with several challenges like fuel factors, security breaches, system failures, and congestion management. With the customers being the most critical asset an airport can have, it is prudent to avert overcrowding at the airports to result in delays, thefts, safety risks that later turn to poor and reviews, and loss of the vital asset. People traveling with airlines have been rising, with 2019 witnessing 4.5 billion passengers using flights worldwide. It is projected that the number will be 40 billion by 2040 (https://aci.aero/news/2018/11/01/acis-world-airport-traffic-forecast-reveals-emerging-and-developing-economies-will-drive-global-growth/). On the other hand, the building of infrastructure and employing more staff could be an option to solve the menace like India is currently doing. Still, it takes time and costs; therefore, intelligent management of passengers could be the most viable approach and thus this paper's aim.
Airports could adopt optimization of resource needs availability in the event of unforeseeable failures such as blackouts occurs. According to Brause, Popa, Koch, Deutschmann, & Hellmann (2020), there have been power outages at airports causing operational lapses causing a bottleneck in passenger handling; it has also been evident that existing emergency power plans were not sufficient, thus improving and addition of the resources is necessary. For instance, Oakland International Airport faced a blackout in 2019 that resulted in baggage claim delays and long security lines. It was evidence of how the airport was not prepared to deal with such a situation https://edition.cnn.com/2019/11/27/us/oakland-airport-power-outage/index.html. Generally, failure to have backup preparedness plans has led to an increased number of passengers failing to reach their flights during such events due to increased waiting time at the service points. Therefore decentralization through blockchains and decisions such as the number of service points that could be dispensed to sub-process and handle passengers without interfering with flight operations could be some of the preparedness results. The whole preparedness system could be made simpler by employing intelligent technologies that can copy the data for use in different mediums in anticipation of such occurrences.
Schultz & Fricke (2017) recommend introducing the agent-based model and stochastic approach to manage passenger crowding tactically. Since efficient passenger handling is paramount for a reliable terminal process, design processes such as finding individual passenger behavior could be applied. Thus, a calibrated and detailed approach with an identification system with optimization abilities is used to help route choice and strategic decision-making. The standard flow-oriented process is flawed; for example, it leads to increased waiting time and security issues. Thus, to determine the black terminal box, significant changes have to be considered to handle passengers efficiently. The stochastic process posits that airports collect data by use of queue measurement system, and by the use of the data predict based on randomness and probability of passengers coming to the airport based on all factors such as weather, season, and expectations, thus employing the necessary to manage the travelers.
The use of a queue measurement system (QMS) in airports to serve passengers is an efficient way of handling travelers. The system can help factors such as letting the customers be aware of the total people in the queue ahead of them; the customer gets to know how much time they are going to wait before service to keep them calm, highlighting of sensor technologies to be implemented to breakdown passenger activity and volume. The organization can collect data on the queue for processing. According to Felkel & Klann (2018), QMS, also known as passenger flow management (PFM), is much advanced and overcomes systems' shortcomings solely relying on measurement technologies such as lack of predictability, lack of flexibility, lack of integrated analytic system, lack of comparison. PFM has several advantages like optimization of waiting time, overhead reduction, and lack of maximization, overall passenger experience improvement. It provides the benefits by integrating platforms like measurement technologies that take users' data from their check-in, availability of taxi services and efficiency, retail within, immigration, security, and the arrival versus departure patterns. The system is also integrated to predict in real-time to alleviate the impacts of bad weather, flights off schedule, and traffic conditions. Forecasting also extends to extensible analytics such as algorithmic IT operations (AIOps) and predicting ways like conditions of days, months, and years ahead. The use of such technology is the future of airlines. It is currently in use in India to beat the upsurge of flight travelers. It outperforms traditional approaches such as mobile lounges that could not survive time due to passengers' increase.
The use of technologies is critical in managing passengers' upsurge but would be less effective if the infrastructure is not added and improved. Airports need to be expanded to accommodate ever-growing travelers and more staff employed. The Indian airports have been overwhelmed by the number of passengers and is predicted to worsen by 2024 (Barde, Pantelias, & Zerjav, 2016). To bring efficiency and quick passenger movement, the government has expansion plans planned to cost up to $ 2 billion according to https://qz.com/india/1520375/indias-bengaluru-airport-is-finally-getting-bigger/. In addition to technology, the best way to fasten services is to increase waiting lounge spaces, improve runways and service stations.
Adopting a self-service program by airports and airlines has partly been implemented. It continues to be affected, reducing overhead, handlers, and long queues through a system known as integrated passenger self-service program (IPSSP). For instance, from the time a passenger books a flight on the company's website to the onboarding time, several airports have implemented IPSSP, thus enhancing passenger flow and improving on passenger experience through the integration of a customer's profile to social media to reduce data collection (Barich, Ruiz, & Miller, 2015). Therefore, the adoption of self-services and its stages lies back to the use of intelligent approaches to managing passengers.
Passenger movement has been a menace in most global airports and therefore finding ways to solve it has been the primary goal of many. This paper has analyzed the predicament and found that intelligent technology is the way forward to efficiently and quickly move flight passengers. This approach is comprehensive and entails using technology preparedness plans like a stochastic process through systems like AIOps, FPM, and IPSSP. The system can analyze situations and forecast future occurrences that could help in decision making, for instance, when and to what extent to increase more infrastructure. Technology is the best method to fasten passenger movement in airports.
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