# Identification of Bottlenecks in Passenger Handling Processes Using Data-Driven Tools
## 1 Introduction
Its modular structure allows for dynamic adaptation based on changing epidemiological conditions, making it a valuable planning tool for public health and border authorities. Efficient management of handling processes at airports is a key factor in ensuring smooth operations and increasing passenger satisfaction. Optimizing these processes is essential to minimize the waiting and congestion that can occur during peak hours. The authors of the paper [21] explore ways to improve these processes, highlighting the importance of technological innovation and reorganization of existing systems. Efficient baggage handling and passenger handling optimization are key aspects to increase the overall operational efficiency of an airport. Practical examples of the use of technological innovations can be found in [22; 23] or [24]. One study [22] focuses on the development of airport technologies. It proposes the implementation of biometrics in the handling processes, which, through the contactless verification of passengers' identities, enables automated screening without the need for airport staff. Both innovations mentioned above are examples of possible streamlining of handling processes by not only increasing the overall fluidity of the processes and reducing waiting times but also providing increased security of the handling processes. Another study [23] describes the emerging concept of the \"smart passenger\", which refers to passengers equipped with smart devices such as mobile apps, biometric belts, digital boarding passes, and other technologies that facilitate interaction with airport systems. Both innovations aim not only to reduce waiting times and increase throughput but also to strengthen the security and resilience of airport operations. In a related direction, one study [24] investigates the use of Self Bag Drop (SBD) technologies as a cost-effective solution for regional airports with limited space and staffing capacity. Using the SIMIO simulation environment, the authors compare conventional check-in scenarios with semi- and fully automated SBD configurations. Their results show that a fully automated SBD system can reduce average passenger waiting times by more than 45% during peak periods, while also increasing throughput and minimizing queue spillover. The study further emphasizes that the dynamic allocation of SBD stations based on passenger arrival patterns can significantly outperform static layouts, especially under uneven or unpredictable demand. These insights reinforce the practical value of automation not only from a technological standpoint but also as a flexible strategy that aligns with airport capacity planning and service quality goals. While high-end simulation platforms and digital twin architectures represent the forefront of airport digitalization, simplified modeling environments, such as Microsoft Excel, continue to offer accessible and flexible tools for operational experimentation, particularly in early-phase planning. As pointed out in [25], digital twin maturity is not solely a function of technological sophistication but rather of how accurately the model captures critical system behaviors and supports purposeful decision making. In this regard, even a probabilistic spreadsheet-based simulation of passenger handling can act as a relevant step toward digitized capacity management, especially for regional airports aiming to balance performance improvements with cost efficiency. Such tools embody the practical spirit of Industry 5.0 by promoting human-centric, modular solutions that are adaptable to real-world constraints without requiring complex infrastructures [1].