Development of an advanced AI-based system for the automatic compilation of the Smart Terminal Journal
SEA (Società Esercizi Aeroportuali di Milano)
Cefriel
Riduzione del Lavoro Manuale
Automatizzando il processo di compilazione del GdS, il progetto ha liberato il 30% della capacità di un team di 9 persone, pari a 2,5 FTE, ottimizzando i tempi e le risorse.
Riduzione degli Errori
Grazie al controllo automatico della consistenza dei dati e alla segnalazione delle anomalie, il sistema ha ridotto quasi completamente gli errori nel GdS, migliorando la qualità delle informazioni.
Riduzione dei Costi di Gestione IT
Il progetto ha portato a una significativa riduzione dei costi di gestione IT, ottimizzando la manutenzione e l’aggiornamento del sistema attuale, e riducendo i costi associati al lavoro manuale e alle rilavorazioni.
SEA (Società Esercizi Aeroportuali di Milano) is a leading company in the management and development of Milan’s airport infrastructure. It operates with the aim of ensuring efficiency, safety, and innovation in airport services.
The ‘Giornale di Scalo’ (Smart Terminal Journal) is a critical tool for tracking and managing airport operations, including information on aircraft movements, passengers, and cargo. However, the current manual process carries a high risk of errors, inefficiencies, and delays in data availability, impacting safety, costs, and operational coordination. Automating this process is essential to ensure greater accuracy and to support more effective management of airport resources.
“The project aims to develop an advanced system based on artificial intelligence (AI) for the automatic compilation of the Smart Terminal Journal. The system will rely on the extraction and classification of data from heterogeneous sources, both structured and unstructured. The solution will include an experimental laboratory phase to validate the developed models and will serve as a preliminary step toward the implementation of an industrial-grade product.
The solution will include an experimental laboratory phase to validate the developed models and will serve as a preparatory step for the implementation of an industrialized product.
Predictive models based on machine learning to estimate the reliability of incoming information, which is often incomplete or contradictory.
Cost optimization model aimed at minimizing the total cost associated with the management of incoming information by SEA operators.
Dedicated IT infrastructure: an experimental environment configured for the training, validation, and testing of the developed solutions.
The project aims to bring about a significant transformation in SEA’s airport operations, enhancing not only internal management but also the overall experience of airport system users.
Expected impacts include:
Increased operational efficiency: achieved through the reduction of time and errors associated with the manual management of the Smart Terminal Journal
Reduction of human errors in the compilation of the Smart Terminal Journal
Technological advancement: the project will lay the foundation for further innovations in airport systems, promoting greater technological integration.
Implementing the proposed solution will bring numerous benefits to SEA, both in terms of operational efficiency and competitiveness. In particular:
– Cost optimization: by reducing time waste and inefficiencies related to manual work.
– Improved safety: through more accurate and reliable management of critical information.
– Increased competitiveness: by positioning SEA as a technological leader in the airport sector through the adoption of innovative solutions.
– Operational sustainability: by enhancing the ability to manage resources more effectively and responsibly.
