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Purpose: The airport infrastructure plays capital importance in the development of national trade. It facilitates the flow of people, goods, and services more quickly. Thus, given its importance, this study seeks to analyze the impact of the Angolan investment in airport infrastructure between 2000 – 2020.Design/methodology/approach: this article presents the results of quantitative and qualitative research, based on narrative review and output of the Auto-Regressive Distributed Lag (ARDL) technique, which aimed to analyze the impact of investment in airport infrastructure on the growth of Angola GDP per capita.Findings: The results of the stationarity tests performed shows mixed integration in both I(0) and I(1), which justifies the used ARDL. Similarly, the bounds test showed that there is a very strong relationship between airport infrastructure investment and GDP per capita growth in the short and long run. However, in the Angola case study, the impact that exists is negative, meaning that airport infrastructure negatively impacts per capita GDP growth in both the short run and in the long run.Research limitations/implications: this research has been among the first to analyze the impact of investment in airport infrastructure on the growth of Angola GDP per capita. Besides the contribution of this research, some limitations are the difficulty to find data of investment and the literature about transportation infrastructure in Angola.Originality/value: the analyze of the impact of investment in airport infrastructure in the growth of Angola GDP per capita is a fundamental step that can help public and private entities in making decisions that aim to improve the management of the Angola transport infrastructure.

Purpose: This study is focused on determination whether the size of an airport influences the airport's policy regarding the amount of aircraft-related airport charges. Additional test were conducted to determine whether airport charges are dependent on airport profile. Design/Methodology/Approach: The sample includes airports located in the European Union that in 2019 served more than 5 million passengers (threshold in accordance with the master EU-level Directive 2009/12/EC, 2009). The data records were also grouped into 3 sections representing large hubs, small- and medium-sized hubs and regional/LCC/charter airports. The airport charges data used for the analysis is supplied by own studies and calculation based on airports individual price lists for 2021. The research hypotheses were verified with the use of the classic regression model and Pearson Correlation Coefficient. Findings: The findings may indicate that larger airports leverage their market position and charge more for aircraft movements. However airports may also apply different policies, depending on whether they belong to small and medium-sized hubs or large ones. Practical Implications: Better understanding of airport pricing policies and their motivations may help: - Regulators – to better adjust the policy to the realities and needs of the market. - Airports – to ensure better and more effective approach airport charges. - Airlines – to better understand airport policy on airport charges and to enforce their positions on these charges more efficiently, including during their consultations. Originality/value: The existing research focuses on aeronautical revenue and airport charges in bulk. The proposed approach is more targeted and offers a more in-depth analysis of the nature of airport charges and their determinants at disaggregated level., peer-reviewed

Given the chip and processor size reduction given in the last decades, added to the cheaper and more computational power of them, digitalization and automation of processes has been a nowadays topic that is slowly but steadily increasing and having bigger presence, creating big extended concepts like Industry 4.0 and all the related topics like robotics or artificial intelligence. For the other side, the aerospatial sector, each time wiht a bigger presene, goes inside a big problem where the actual infrastructure is getting small and they need, from one side, optimize the system and from the other, reduce pollutant emissions to the minimum to reach the net-zero 2050 goal for 2050, when the greenhouse effect emissions are expected to be zero o that the created emissions are re-absorbed by the nature and not emitted. Given this situation, in this project it will be shown actual situation of both the aerospace sector and the robotics, and the possible applications can be done on this sector. Also, a little study will allow us to corroborate that the robotic systems have big importance to accomplis the incoming challenges on the aerospatial sector. Also, a series of prototypes, starting from a simple one without graphical interface, going through another with a graphical interface and finally to one controlled by using virtual reality glasses, will be developed and tested as a proof of concept of a robot with applications on the sector, using always technologies that allow an easie reproduccion or platform change to agilize all the future development. All of this with the objective of proving that nowadays robotics does not present a big challenge for solutions development to the aerospace sector. Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura

As the title suggests, the project is about applying image processing techniques to airportmanagement. Concretely, about the recognizement of aircraft by detecting their registra-tion.The first thing to do to get the registration of an aircraft is taking a photo of it. In order todo that, a motion detector takes photos of the aircraft when the aircraft is in front of thecamera. The photos are sent to a server that is used as a storage unit, then the clientdownloads groups of photos to begin the processing stage. The first step is an objectdetection deep learning algorithm which finds and identifies all the objects that appear ineach photo. Knowing the position and the size of the airplanes that appear in each photo,the client chooses the best three photos.The selected photos advance to the next processing step which consists in a deep learn-ing optical character recognition (OCR) algorithm. The result of processing photos withthe OCR is the transcription of all the texts that appear in the image. The only interestingtexts for this project are the registrations, so post processing filters are in charge of dis-carding every text that does not look like a registration. Finally, the system decides whichregistration appears in the image by comparing the results of the OCR to a list of possibleregistrations. By using this system, a 91% accuracy has been reached with a group of 66images.The main aims of the system are the control of the take off and landing operations in nocontrolled airports and the control of the parkings and hangars to locate any aircraft in theairport using the security camera images. Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura

L'any 2019 l'Aeroport Josep Tarradellas Barcelona-El Prat va estar a 2 milions de passatgers d'arribar al seu límit de capacitat fixat en 55 milions. Amb les previsions d'usuaris realitzades i sense tenir en compte la pandèmia s'observa com en qüestió de poc més d'un any s'hagués arribat en aquest límit. Per evitar el col·lapse de la infraestructura barcelonina, l'estudi en qüestió proposa utilitzar l'Aeroport de Reus per tal de cobrir l'excés de demanda. A més, també proposa 3 models de gestió pels dos aeroports: el model actual en xarxa d'AENA, el model d'Aeroports de Catalunya o bé, un model mixt, on l'Aeroport de Barcelona forma part d'AENA i el de Reus d'Aeroports de Catalunya. Aquests models han estat avaluats a partir d’una anàlisi multicriteri. El model de gestió millor puntuat amb la ponderació aplicada juntament amb el model actual, que ha servit com a base de referència, han estat analitzats econòmicament i mediambientalment. D'aquesta manera s'ha observat que la seva aplicació és viable i que genera un impacte negatiu al medi ambient. Per acabar, s’ha donat èmfasi a la situació actual de pandèmia i s’ha fet una previsió de la demanda dels dos aeroports en tres nivells diferents: any 2021, període 2021-2025 i període 2026-2030. Aquests pronòstics han tingut en compte els estudis més recents, en termes de previsions de tràfic, d’entitats de renom com EUROCONTROL, ACI i IATA. In 2019, Josep Tarradellas Barcelona-El Prat Airport was at 2 million passengers to achieve its limit of capacity, which is established at 55 million passengers. With the user forecast and without taking into account the pandemic, it is observed how the airport would have arrived at its limits in less than a year. In order to avoid the Barcelona Airport collapse, this study suggests using Reus Airport to supply the exceeding demand. Moreover, it suggests 3 management models for both airports: the current model in AENA network, the model of Aeroports de Catalunya or a mixed model, where the Barcelona airport belongs to AENA and the Reus airport belongs to Aeroports de Catalunya. These models have been compared in a multi-criteria analysis. The best ranked management model with the applied ponderation and the current model, which has been used as a basic reference, both have been economically and environmentally analyzed. In this way, it has been observed that is viable the application and it causes a negative environmental impact. Finally, the actual pandemic has been considered. Therefore, a passenger traffic forecast for both airports has been done in 3 different periods of time: 2021, 2021 to 2025 and 2026 to 2030. These forecasts have taken into account the most current studies in terms of traffic prediction, developed by commonly known organizations such as EUROCONTROL, ACI and IATA.

As each year the number of passengers in the world grows, the airports get crowded and closer to their limit capacity. When they arrive at this point, they have to look for a solution to increase the capacity of the airport. The easiest solution is to expand the airport creating new terminals, but this solution is very expensive and sometimes is not feasible because the airport could have a limited space. Another solution is to optimise the current infrastructure in order to increase its capacity. Another possible solution that has arisen in the last years is the use of technology to increase the capacity of airports. The digital transformation brings a lot of possible solutions to the airport to improve the processing capacity of the processes that passengers have to go through when travelling by airplane. These solutions, apart from having the possibility of increasing the capacity of the airport, they could also be helpful to increase the passenger satisfaction and make the airport more competitive that nearby airports

The small-to-medium sized Malta International Airport (MIA) is the only airport in Malta, especially in terms of its footprint, and is considered one of the world’s most scenic landings, according to a 2016 poll. The annual passenger turnover is approximately 16 times the country’s population. MIA’s unique features include its proximity to the urban conservation area of Luqa, as well as that town’s other residential and business facilities, and also to the southern coast of Malta and the unique ecological habitats it supports. Its impacts range from noise to atmosphere pollution and, potentially, pollution of the coastal waters, in the eventuality of an air traffic accident. On the basis of the national strategic vision that Malta evolves into an expanding hub in the centre of the Mediterranean, significant investment is earmarked for MIA, including initiatives impacting security, the environment and energy., peer-reviewed

The aim of this Project is to analyze and specify all the requirements needed to make an intelligent airport and the definition of that term with the actual state of technology. we have almost 20.000 airports around the world, Aena has a network of 68 airports and presence in other major infrastructures of the industry. This gives us a wide range of types of buildings even under the same control and that usually translates into a difference in management, hence the importance to select a study case, our case will be the South Tenerife’s airport, a middle airport that has a strong presence in a network that move a total of 275,2 millions of passengers in 2019. Nowadays, advanced control systems are widely used for airport infrastructures, usually with different protocols and architectures for each one of them. There are also many management software packages with specific applications for airport activities. This creates a complex scenario, composed of many systems made up of subsystems and a wide flow of data generated and handled with incompatible formats. This makes it necessary to have a worldwide standard, which allows the integration of systems and converge in the digitalization of airports. A digitized airport requires that all processes be automated and computerized. Then they must be able to integrate the systems into a communication network that allows the exchange of data and the development of integrated management packages in an advanced system on a higher level. Creating a standard and digitizing information for exchange between systems that require establishing memory map formats for each subsystem, including capacity, definitions, and ranges of variables. It is necessary to establish the subsystems that make up the airport, of which we highlight the main ones: • Buildings (Terminal, Tower, Handling, Hangar, Warehouse), Platform and Urbanization • Systems: Electrical, Water, Telecommunications, Civil Protection, and Avionics. • Companies: Companies, Catering, Fuels, Maintenance, Cleaning, and Security. • Flows: Cargo, Personnel, Passenger, and Baggage. All these systems provide the information needed for the airport's integrated management system (AMS: Airport Management System). The required technology is available and there are more and more hardware/software solutions, so we must propose a guide of protocols and tools for integration and processing. Given the amount of data to be managed, the intelligence of these systems lies in establishing pre-processed data for subsequent treatment with Big Data techniques and generating "machine learning" models. The integration of systems such as SITA or Xovis is required to provide a global solution to flow management problems, providing the necessary information to the entire network and the AMS, which guarantees to adapt quickly to any situation with an efficient and safe operation. The next step is to create models for these systems and develop the associated interfaces. Currently, there are companies such as SITA, Wonderware, Schneider that provide management software developments that work with standardized protocols such as ModBus or Bacnet, the latter being very widespread. El objeto de este proyecto es analizar y especificar los requerimientos necesarios para poder hacer un aeropuerto inteligente y la definición de dicho término dentro del marco de la actual tecnología. Actualmente existen cerca de 20.000 aeropuertos alrededor del mundo, Aena tiene una red de 68 aeropuertos y presencia en otras grandes infraestructuras de la industria. Esto significa un variado rango de tipos de aeropuertos, incluso bajo la misma propiedad, lo que se traduce en multitud de variantes de gestión aeroportuaria, por eso consideramos necesario elegir un aeropuerto tipo. Hemos seleccionado el aeropuerto Tenerife Sur, cercano a la media con gran presencia dentro de la red de Aena, la red movió un total de 275,2 millones de pasajeros en 2019. Hoy en día está extendido el uso de sistemas de control avanzados para las infraestructuras aeroportuarias, normalmente con protocolos y arquitecturas distintas. También hay multitud de paquetes de software de gestión con aplicaciones específicas para las actividades aeroportuarias. Esto establece un panorama complejo, compuesto por una gran cantidad de sistemas formados por subsistemas y un amplio flujo de datos generados y manejados con formatos incompatibles. Lo que hace necesario la existencia de un estándar mundial, que permita la integración de sistemas y converger en la digitalización de los aeropuertos. Un aeropuerto digitalizado requiere primero que todos los procesos estén automatizados e informatizados. Que se puedan integrar en una red de comunicaciones que permita el intercambio de datos y el desarrollo de paquetes de gestión integrada en un sistema avanzado de nivel superior. Crear un estándar y digitalizar la información para su intercambio entre sistemas, requiere establecer formatos de mapas de memoria por cada subsistema, incluyendo capacidad, definiciones y rangos de variables. Es necesario establecer los subsistemas que conforman el aeropuerto, de los que resaltamos los principales: • Edificaciones (Terminal, Torre, Handling, Hangar, Almacén), Plataforma y Urbanización. • Sistemas: Eléctrico, Agua, Telecomunicaciones, Protección Civil y Aviónica. • Empresas: Compañías, Combustibles, Mantenimiento, Limpieza y Seguridad. • Flujos: Cargas, Personal, Pasaje y Equipaje. Todos estos sistemas proporcionan información necesaria para el sistema de gestión integrada del aeropuerto (AMS: Airport Management System). La tecnología requerida está disponible y cada vez hay más soluciones de hardware/software, por lo que debemos proponer una guía de protocolos y herramientas de integración y procesado. Dada la cantidad de datos a gestionar, la inteligencia de estos sistemas reside en establecer preprocesados de datos para su posterior tratamiento con técnicas de Big Data y generar modelos de “machine learning”. Se requiere la integración de sistemas como SITA o Xovis para proporcionar una solución global a los problemas de gestión de flujos, facilitando la información necesaria a toda la red y al AMS, que garantice adaptarse rápidamente a cualquier situación con un funcionamiento eficiente y seguro. El siguiente paso es crear modelos para estos sistemas y desarrollar las interfaces asociadas. Actualmente existen compañías como SITA, Wonderware, Schneider que proporcionan desarrollos de softwares de gestión que funcionan con protocolos normalizados como ModBus o Bacnet, este último muy extendido.