CBL - Campus del Baix Llobregat

Projecte llegit

Títol: Design of a software tool to support the LECB TMA supervisor

Estudiants que han llegit aquest projecte:

Director/a: PRADES GIMENO, ALBERT

Departament: FIS

Títol: Design of a software tool to support the LECB TMA supervisor

Data inici oferta: 07-02-2026     Data finalització oferta: 07-10-2026


Estudis d'assignació del projecte:
    GR ENG SIST AEROESP
Tipus: Individual
 
Lloc de realització: EETAC
 
Paraules clau:
Network Manager, API, Flight, Python, arrival traffic prediction, JSON, air traffic concepts.
 
Descripció del contingut i pla d'activitats:
From a TMA supervision perspective, the aim is to view aircraft flying towards LEBL well in advance, at a European or even global level.

The objective is to detect overloads by analyzing traffic flows in a graphical way and to be able to take tactical balancing measures with adjacent sectors or within the TMA (route changes or speed reductions for certain traffic in order to space them out).

The tools to be used will consist of recurring calls to the ENAIRE B2B API (Eurocontrol Network Manager API) and API OpenSky, followed by JSON data filtering and analysis using Python.

A graphical application will then be developed to visualize the movement of aircraft with destination LEBL, based on a predefined update interval based on entry20 intervals, similar to CHMI Eurocontrol app.
 
Overview (resum en anglès):
This Bachelor's Thesis describes the design, development, and validation of GRAPA, a visual assistance tool aimed at optimizing tactical supervision and decision-making within the Barcelona TMA. The primary objective of the project is to mitigate the high workload and cognitive effort assumed by air traffic controllers and supervisors when monitoring continuous sector balancing and arrival traffic flow (operations associated with the "entry20" sector capacity concept). Traditionally, interpreting these flows required consulting complex alphanumeric lists; through GRAPA, this information is transformed into an interactive, dynamic, and easily interpretable situational map.

To achieve this objective, the adopted methodology is based on the integration and fusion of heterogeneous aeronautical data sources through the development of a backend processing engine using Python. On the one hand, the extraction of strategic flight plan data from the PR24 API, managed by Enaire and the Network Manager, is automated. On the other hand, this information is correlated with real-time ADS-B kinematic data obtained via the OpenSky Network REST API, capturing the aircraft's state vectors. This asynchronous processing feeds a web environment developed with the Flask framework, which projects an optimized graphical interface. Key implemented features include automated flight counting per control sector, dynamic filtering of aircraft based on their assigned IAF, and predictive flow visualization.

The obtained results confirm the technical feasibility and operational suitability of the tool. The system has demonstrated a solid capacity to unify strategic forecasting with tactical tracking, reducing the uncertainty inherent in holdings and traffic overlaps. GRAPA has undergone a rigorous validation process at the Barcelona ACC, successfully passing operational tests conducted by air traffic control experts. The high level of acceptance and the demonstrated improvements in flow management have sparked strong interest from the national air navigation service provider's top management. In conclusion, GRAPA not only meets the initial requirements but also positions itself as a scalable technological solution, paving the way for its future homologation and potential operational deployment in control centers.

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