cHALLENGE
#2
How can we?
OPTIMIZE THE EFFICIENCY OF SERVICES AND PROCESSES IN THE MANAGEMENT OF MANNED AND UNMANNED AIR TRAFFIC
Context / Problem
ENAIRE manages a complex and interdependent system that provides air navigation services, including airspace management, real-time traffic control, balancing flight demand and airspace capacity, and providing aeronautical information. All these elements work in coordination to ensure air safety, reduce flight delays, and minimize environmental impact.
Increased air traffic, the incorporation of drones, international conflicts, and increasingly unpredictable weather phenomena are making air traffic management more complex. This situation is putting current models, which rely heavily on human intervention, to the test.
Increased air traffic, the incorporation of drones, international conflicts, and increasingly unpredictable weather phenomena are making air traffic management more complex. This situation is putting current models, which rely heavily on human intervention, to the test.
Opportunity / Expected objectives
ENAIRE is seeking technological solutions to automate tasks and processes that help anticipate potential critical situations and facilitate decision-making in order to optimize the provision of its air navigation services. Proposals based on artificial intelligence will be particularly valued, provided they comply with the regulatory framework and meet the strict safety requirements of the air traffic management environment.
Guiding examples
- Intelligent automation of flight and aeronautical information services, such as weather information or runway and route status, to optimize the provision of critical information and reduce the workload of air traffic controllers.
- Development of advanced applications for Aeronautical Information Services (AIS), with the aim of improving their accessibility, accuracy, and usefulness for general aviation users.
- Predictive and early detection systems to anticipate airspace congestion or abnormal behavior that affects safety.
- Generation of synthetic data and development of artificial intelligence algorithms to support drone traffic management, especially when there is insufficient real data available for model training.
- Design of systems for the safe and equitable management of airspace, ensuring fair access for all drone operators and identifying and tracking unmanned aircraft in real time within controlled airspace.