Advances of Artificial Intelligence in Aeronautics
Abstract. - The use of artificial intelligence (AI) in recent years has allowed the development of a large number
of applications in practically all areas of human knowledge. However, the application is relatively new in
aeronautics, and products are already optimizing the skills and capabilities of the personnel who command it.
This paper reviews the scientific literature on the advantages, disadvantages, and aspects to consider
regarding the application of AI techniques in aeronautical processes ranging from construction, navigation,
and security against attacks on communications and climate changes that may affect the navigation system. AI
developments provide new advantages and challenges for navigation every day. On the one hand, these
techniques support flight independence until achieving absolute autonomy. Still, on the other hand, they also
incorporate specific vulnerabilities and concerns about the increased use of computer and digital
communication media that are prone to attacks by malicious individuals or organizations.
Keywords: Aeronautics, Artificial intelligence, machine learning, autonomous navigation.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
Sánchez Byron
https://orcid.org/0009-0005-5905-2782
bysanval@hotmail.com
Ejército Ecuatoriano
Shell-Ecuador
Resumen: El uso de la inteligencia artificial (IA) en los últimos años ha permitido el desarrollo de una gran
cantidad de aplicaciones en prácticamente todos los ámbitos del conocimiento humano. En la aeronáutica la
aplicación es relativamente nueva y ya existen desarrollos que optimizan las destrezas y capacidades del
personal que lo comanda. En este trabajo se presenta una revisión en literatura científica de las ventajas,
desventajas y aspectos a considerar en torno a la aplicación de técnicas de IA en procesos de la aeronáutica
que van desde la construcción, navegación y seguridad ante ataques en comunicaciones y cambios climáticos
que pueden afectar al sistema de navegación. Los desarrollos en IA cada día aportan nuevas ventajas y
desafíos para la navegación, por una parte, estas técnicas apoyan la independencia del vuelo hasta lograr la
autonomía absoluta, así como también, incorporan ciertas vulnerabilidades y preocupaciones en torno a un
mayor uso de medios informáticos y comunicaciones digitales que son propensas a ataques por parte de
personas u organizaciones malintencionadas.
Palabras clave: Aeronáutica, inteligencia artificial, aprendizaje automático, navegación autónoma.
Avances de la inteligencia artificial en la aeronáutica
34
Received (01/11/2022), Accepted (11/05/2023)
Duran Daniel
https://orcid.org/0009-0008-3022-129X
mauricio87205@hotmail.com
Ejército Ecuatoriano
Shell-Ecuador
Martínez Kevin
https://orcid.org/0000-0003-1124-7319
kevinmng96@gmail.com
Ejército Ecuatoriano
Shell-Ecuador
Viera Washington
https://orcid.org/0000-0002-9118-3388
kanes.dj@gmail.com
Ejército Ecuatoriano
Shell-Ecuador
https://doi.org/10.47460/athenea.v4i12.56
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
35
I. INTRODUCTION
Artificial intelligence has been incorporated into various human activities, also used in the aeronautical and
aerospace industry, mainly to improve the efficiency and safety of flight operations. Its use in automation
through flight management systems and autopilot has yielded excellent results. Despite the implementations
of automatization, the effectiveness and safety of a flight also depend on human decision-making, aspects that
remain crucial to ensure flight safety and whose appearance has yet to be replaced.
The aerospace industry has employed artificial intelligence despite uncertainties about the confidence that AI
will provide when faced with critical situations, which are currently the responsibility of aviation experts.
Guidelines, recommendations, and guidance have been proposed in the Research Manual on Applications of
Artificial Intelligence in Aviation and Aerospace; In this work, the applications of AI in aviation and aerospace
are addressed. The adoption of AI in this sector is a growing trend and focuses mainly on reducing human
error and improving its efficiency[1].
According to Figure 1, artificial intelligence in aviation has been employed in air combat, the aeronautical
industry, cognitive systems, aircraft maintenance repair, data analysis, defect detection, and deep learning in
defect detection[2].
AI technology also supports the detection and resolution of onboard problems during flight, reducing the risk
of falls and accidents by influencing the predictive stability behavior of aircraft. In addition, implementing
advanced monitoring and tracking systems, such as predictive maintenance, allows airlines to identify and fix
logistical issues before they cause flight disruptions. As a result, technology has been essential to ensure a
better experience for the crew and in the operation of the aircraft.
Information collected on an aircraft is stored and used in air accident cases to generate reports and obtain
evidence. The analysis of data and knowledge of the flights are already carried out efficiently with artificial
intelligence applications, which are capable of performing very complex studies that involve all the electronic
data of the entire aircraft allowing to provide a better result in the determination of evidence in accidents or
causes of accidents[3].
AI technology also supports the detection and resolution of onboard problems during flight, reducing the risk
of falls and accidents by influencing the predictive stability behavior of aircraft. In addition, implementing
advanced monitoring and tracking systems, such as predictive maintenance, allows airlines to identify and fix
logistical issues before they cause flight disruptions. As a result, technology has been essential to ensure a
better experience for the crew and the operation of the aircraft.
Fig. 1. A bibliometric review of the terms "Aeronautical Artificial Intelligence" in the SCOPUS Base (36 articles)
graphed with VOSviewer®.
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
36
Information collected on an aircraft is stored and used in air accident cases to generate reports and obtain
evidence. The analysis of data and knowledge of the flights are already carried out efficiently with artificial
intelligence applications, which are capable of performing very complex studies that involve all the electronic
data of the entire aircraft allowing to provide a better result in the determination of evidence in accidents or
causes of accidents[3].
Fig. 2. Technological aspects addressed by Industry 4.0 in aviation.
This document describes applications that use AI and corresponds to the field of the aeronautical industry in
the development section. Then, in the Methodology section, it is detailed how the reference information was
obtained. Then, in the Results section, an analysis of the findings and trends in the use of AI in the field of
aeronautics is presented; finally, the conclusions are offered.
II. DEVELOPMENT
This section describes some current applications implemented in the aviation industry according to an
overview of the advances and applications that use AI to solve problems in aviation and its previous
manufacturing processes. The information provided in this section allows researchers and professionals to
know the state and influence of AI in aircraft navigation, control, manufacturing processes, management, and
maintenance systems.
From the review of scientific literature, it was evident that the most relevant topics in which AI is used are
machine learning and neural networks. The use of AI allows for improving the efficiency of the tasks. In
addition, the functions and applications are also evolving, such as new projects under development, such as
the implementation of autonomous air taxis and air transport of large and small objects.
Artificial intelligence has had a significant impact on the aviation industry. It has made it possible to improve
flight safety by detecting potential problems and providing proactive solutions for securing them, as well as
increasing operational efficiency by optimizing routes and reducing fuel consumption in the face of factors
such as unfavorable weather conditions or others[7].
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
37
Flight safety has been improved with AI, enabling more accurate and faster real-time inspections of aircraft
and equipment and detecting anomalous patterns in maintenance data. AI allows for optimizing air traffic
management, flight planning, and fleet management, ensuring more efficient and safe air travel [6]. The
aviation industry faces challenges of unscheduled maintenance, repair, and overhaul (MRO) costs. It is turning
to advanced technologies such as artificial intelligence to improve efficiency and reduce costs by providing
predictive analytics to identify problems before they occur, reducing unscheduled repairs and thus
revolutionizing multiple aviation industry processes[6].
Tabla 1. Influence of AI on multiple aspects of the field and development of aeronautics.
The table above highlights eight aspects artificial intelligence has dramatically impacted aeronautics. Most of
these aspects focus on improving efficiency, safety, and quality in the aviation industry. One of the highlights is
optimizing efficiency in air traffic management, route planning, and fuel management. Artificial intelligence has
enabled air traffic controllers to make more informed decisions and has helped reduce airport waiting time
and improve flight punctuality. Security has also been an important area where artificial intelligence has
significantly impacted aeronautics. AI-based predictive aircraft maintenance technology can detect potential
problems before they occur, reducing the risk of accidents. In addition, the detection of objects on the track
has been improved with AI, reducing the risk of collisions and other accidents. The development of
autonomous aircraft has also been possible thanks to artificial intelligence, which has led to greater efficiency
and safety in the aviation industry. In addition, AI has been used in advanced data analysis, pilot training,
maintenance and repair management, quality control and testing, and aircraft design and simulation.
AI is used in various applications, from optimizing flight planning to improving safety and efficiency in air
traffic management. AI assists managers (airline/airport managers, air traffic management) in a wide range of
air traffic and aviation system applications (pilots, air traffic controllers, airport operators, flow controllers), also
faces new tasks, energy transition, integration of new air traffic components and system difficulties in the face
of traffic disturbances [8]. For example, optimizing flight planning using AI enables airlines to improve aircraft
utilization and minimize delays. In addition, AI can also aid in air traffic management, where it is used to
improve the safety and efficiency of flight management by analyzing data in real time and providing helpful
information for air traffic controllers[9] [1].
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
38
AI is also being used to improve security at airports, for example, to identify suspicious objects by analyzing
images obtained from surveillance video cameras and scanning systems. In addition to military pilots, the
safety of the airspace system also depends on technology and equipment used in the aerospace industry,
including radars, communications systems, and navigation and good coordination among employees of the air
traffic control system. Furthermore, the implementation of advanced technologies such as satellite air traffic
control (SATCA) and flight information systems (FIS) help improve the efficiency of the air traffic control system
by providing excellent safety for passengers and flight teams[10].
Education and training of ATCS employees are essential to ensure the safety of the airspace system.
Continuous training in the latest techniques and technologies is critical to keep employees up-to-date and able
to respond to emerging situations. Artificial intelligence has great potential to improve air traffic management.
AI can help improve efficiency in air traffic, increase infrastructure capacity, reduce delays, and improve safety.
Some AI applications in Air Traffic Management (ATM) include route optimization, congestion forecasting, and
runway capacity improvement[11].
Air traffic management will become increasingly complex due to the growth and increased complexity of
aviation and must be improved to maintain aviation safety. However, with significant improvement in this area,
the safety objectives defined by international organizations can be achieved, and the risk of new incidents or
accidents can be anticipated [12].
It is also important to note that introducing AI in ATMs raises some challenges and concerns, especially
concerning data privacy and security, liability in case of errors, and the need for proper regulation. It is,
therefore, essential to address these challenges to ensure an effective and safe implementation of AI in air
traffic management. Furthermore, since AI can analyze large amounts of data and improve flight planning, fleet
management, and cost optimization, it can also help airlines deliver better customer service by personalizing
offers and resolving issues more efficiently.
NASA aviation research is exploring the possibility of using XAI technology to improve safety and efficiency in
air transport of the future. Explainable AI (XAI) allows humans to understand how decisions are being made in
autonomous systems, increasing trust in them and reducing the risk of unwanted errors. In addition,
explainable AI can also be useful for the certification of autonomous systems and to ensure that appropriate
regulatory standards are met. NASA aims to create a future in which autonomous vehicles can operate safely
and efficiently in airspace, reduce congestion, and improve flight safety. XAI technology plays a crucial role in
this goal by enabling humans to understand how decisions are being made in autonomous systems and
providing greater transparency and trust in them [13, 14].
As the century has progressed, systems with AI have been more accepted and implemented for their
versatility and relatively low implementation costs. The most representative benefit is the time gained with AI
allowing tasks that previously required hours of manual work to be solved with algorithms quickly. The
aerospace industry will also adopt the trend described above, so the lines of research in AI for autonomous
applications may stand out with a more significant impact in academia[15].
In aeronautics, there are innovative technical and organizational systems called intelligent aviation systems,
which provide more safety during the flight of an aircraft. The reason behind its development is the need to
collect statistics on the leading causes of air accidents, such as the human factor, equipment failure, and
external factors. A scientific problem related to assessing and predicting the threat of an accident is
addressed. To solve this, it is suggested to use artificial intelligence to identify and prevent the immediate
causes of an accident. These systems' technical characteristics, properties, and operating principles are
described in detail, including intelligence, information, speed, controllability, the interdependence of
subsystems, threat identification, accident prediction, and stopping [6].
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
39
With the introduction of new aviation technologies and new concepts of airspace organization, it seeks to
provide communication between the airport and the aircraft. GSM technology checks weather conditions,
runway parameters, and air traffic to reduce human errors and manual efforts. Then, before landing, the
aircraft's arrival time is announced automatically [12]. The prospects of military aviators It is claimed that
advanced technology in autonomy and artificial intelligence will likely result in the creation of pilotless aircraft
and that this technological change could make military pilots a thing of the past.
Another important application of AI in aviation is data analytics. For example, AI can analyze large amounts of
flight and aircraft maintenance data to identify trends and patterns, which can help predict failures and
improve maintenance efficiency [12]. In the future, AI is expected to play an increasingly important role in
aviation, helping to make air travel safer, more efficient, and more sustainable. With AI, it is possible to imagine
a future in which airports run more smoothly and efficiently, flights are safer and more comfortable, and the
aviation sector has a much smaller environmental impact.
Table 2 provides valuable information on implementing artificial intelligence in aviation in different countries
worldwide. Leading countries in the aviation industry, such as the United States, China, and France, are leading
the way in implementing artificial intelligence in aviation. Most AI projects in aviation focus on improving safety
and efficiency, including optimizing air traffic management, detecting anomalies, and monitoring aircraft health.
AI-powered projects are being carried out by market-leading airlines and aircraft manufacturers, suggesting
that the industry is leading innovation in this area above academia.
Tabla 2. Examples of AI in applications and projects in different countries around the world.
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
40
IV. RESULTS
The information presented in this paper presents essential findings on implementing artificial intelligence (AI)
in the aviation industry. It is generally recognized that AI has significantly impacted aeronautics, improving
efficiency, safety, and quality in the industry. AI can process large amounts of data and perform complex
analyses to make accurate and fast decisions. However, the importance of supervision and regulation in
implementing AI in aeronautics is also highlighted. Furthermore, it is recognized that AI can present risks if its
use is not adequately monitored, and it is necessary to ensure the safety and well-being of all those involved in
the aviation industry. Therefore, emphasis is placed on the need for proper regulation and close supervision
to ensure that the implementation of AI in aeronautics is safe and effective.
The findings presented indicate that AI can be a valuable tool to improve efficiency and safety in the aviation
industry. Still, its implementation must be adequately monitored and regulated to minimize potential risks.
Text in Calibri number 10. They must be those aspects product of the objectives set. The figures must have a
description in the paragraphs near them. This same section includes the discussions of each result. Everything
must be written in a harmonious and organized way.
III.METHODOLOGY
The reference information was obtained from scientific literature obtained in repositories and scientific
journals in the fields of engineering. In addition, a PRISMA review was carried out in which 15 documents were
included for the study from a review of 116 papers from 4 scientific bases Web of Science, Science Direct,
SCOPUS, and IEEE Xplore. The workflow is visualized in Figure 3.
Fig. 3. Review workflow according to PRISMA methodology.
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
41
CONCLUSIONS
The implementation of artificial intelligence in aeronautics has significantly improved the industry's efficiency,
safety, and quality thanks to its ability to process large amounts of data and perform complex analyses.
However, it is essential to note that aeronautics implementation requires close oversight and regulation to
ensure the safety and well-being of everyone involved in the aviation industry. AI can present risks if its use
needs to be adequately monitored.
Proper regulation and close oversight are necessary to ensure that the implementation of AI in aeronautics is
safe and effective. This implies that regulatory authorities and aircraft manufacturers must work together to
establish clear standards and robust oversight policies to ensure aviation safety and the well-being of those
involved in the aviation industry.
Future applications of artificial intelligence in military aviation represent a significant advance in capability,
efficiency, and operational safety. For example, AI can potentially improve the accuracy and speed of target
reconnaissance and tracking systems, allowing military forces to identify and neutralize threats more
effectively. In addition, AI algorithms can optimize flight paths and strategic resource deployment, maximizing
the efficiency of military operations.
REFERENCES
[1] S. Cuellar, C. Medina y P. Mojica, Artificial intelligence and aerial traffic control, Quito: Superintendencia de
Industria y Comercio, 2017.
[2] Américan Express, «Aplicaciones de la inteligencia artificial en la aeronáutica,» 6 agosto 2018. [Online].
Available: https://www.americanexpress.com/es-mx/negocios/trends-and-insights/articles/aplicaciones-de-la-
inteligencia-artificial-en-la-aeronautica/.
[3] E. Gimenez, «El impacto de la Inteligencia Artificial en la aviación,» Aviacionline, [Online]. Available:
https://www.aviacionline.com/2017/05/el-impacto-de-la-inteligencia-artificial-en-la-aviacion/.
[4] Mordor Intelligence, «Mercado de inteligencia artificial y robótica en el sector aeroespacial y de defensa:
crecimiento, tendencias, impacto de covid-19 y pronósticos (2023 - 2028),» Mordor Intelligence, 2023. [Online].
Available: https://www.mordorintelligence.com/es/industry-reports/artificial-intelligence-market.
[5] M. Romero, La Industria 4.0 en el sector aeronáutico, Sevilla: Universidad de Sevilla, 2021.
[6] Chávez, Cesar, «Ciberseguridad en aeropuertos y compañías de aviación civil,» Segurilatam, 18 mayo 2017.
[Online]. Available:
https://www.segurilatam.com/seguridad-por-sectores/puertos-y-aeropuertos/ciberseguridad-en-aeropuertos-
y-companias-de-aviacion-civil_20170518.html.
[7] L. Caballero, J. García Mestanza y E. Cruz Ruiz, «Ciberseguridad: Las aplicaciones de rastreo de vuelos bajo
la percepción del turista,» Málaga, Facultad de Turismo. Universidad de Málaga, 2018, pp. 354-368.
[8] P. Meller, ESTRATEGIA INDUSTRIA 4.0-Diseñando el Chile del Futuro, Chile: Asimet, 2020.
[9] A. del Corte Valiente, J. Espinosa y D. Mesa, Sistema de control en plataforma aeroportuaria, Madrid:
Congreso de la Red Iberoamericana de Investigación en el Transporte Aéreo, 2011.
[10] Aviación Civil, «ENR 1.6 Servicios y procedimientos de vigilancia ATC,» s.f. [Online]. Available:
http://www.ais.aviacioncivil.gob.ec/ifis3/aip/ENR%201.6.
[11] Cordis, «Inteligencia Artificial transparente y automatización de los sistemas de gestión del tráfico aéreo,»
2022. [Online]. Available: https://cordis.europa.eu/article/id/442199-building-trust-in-air-traffic-management-
ai/es.
[12] G. Carrion, Gestión del tráfico aéreo. Modelo de optimización e implementación, Barcelona: Escuela
Técnica Superior de Ingeniería Industrial de Barcelona, 2016.
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
ISSN-E: 2737-6419
Athenea Journal,
Vol. 4, Issue 12, (pp. 34-42)
42
[13] A. Duval, Explainable Artificial Intelligence (XAI), Warwick: University of Warwick, 2019.
[14] Automática y Automatización, «AEI 521 - La Industria 4.0 en el sector aeroespacial,» 27 julio 2020.
[Online]. Available:
https://www.automaticaeinstrumentacion.com/texto-diario/mostrar/2734316/aei-521-industria-40-sector-
aeroespacial.
[15] J. Gerlings, A. Shollo y I. Constantino, Reviewing the Need for Explainable Artificial Intelligence (xAI),
Copenhague, 2020.
THE AUTHORS
Byron Marcelo Sánchez Valverde, Aviation Captain of the Army,
Ecuadorian Army, Army Aviation Group No. 44 "PASTAZA.” Bachelor's
degree in Military Sciences from the "Eloy Alfaro" Military School.
International Diploma in Teaching Competencies from Tecnológico de
Monterrey-Cambridge (2014). Chief Officer of the Logistics section of
GAE44 "PASTAZA.” Research areas: Military aviation, pedagogy,
languages, and human resources.
Daniel Mauricio Durán Gómez, Army Aviation Captain, Ecuadorian
Army, Army Aviation Group No. 44 "PASTAZA". Bachelor's degree in
Military Sciences from the "Eloy Alfaro" Military School. Chief Officer of
the Human Resources section of GAE44 "PASTAZA.” Research areas:
Military aviation, pedagogy, languages, and human resources.
Martínez Castelo Kevin Orlando, Army Aviation Second Lieutenant,
Ecuadorian Army, Army Aviation Group No. 44 "PASTAZA". Bachelor's
degree in Military Sciences from the "Eloy Alfaro" Superior Military
School. Assistant Intelligence Officer 2019-2021. Research areas:
Military aviation, pedagogy, languages, and human resources.
Viera Pilco Washington Alexander, Army Aviation Second
Lieutenant, Ecuadorian Army, Army Aviation Group No. 44 "PASTAZA.”
Bachelor's degree in Military Sciences from the "Eloy Alfaro" Superior
Military School, Universidad de las Fuerzas Armadas "ESPE" (Ecuador).
Diploma in Education Sciences (Colombia). Transportation Officer and
ICT Officer of Army Aviation Group No. 44 "PASTAZA.”
Sánchez B. et al. Advances of Artificial Intelligence in Aeronautics.
