Descrizione del progetto
Miglioramento della gestione del traffico aereo attraverso la collaborazione dell’apprendimento automatico su set di dati privati
La gestione del traffico aereo (ATM) può trarre grandi vantaggi dallo sfruttamento informatico protetto di grandi set di dati privati appartenenti a diverse parti interessate. Attualmente, tuttavia, c’è una certa riluttanza a condividere dati sensibili. Il progetto AICHAIN, finanziato dall’UE, propone un concetto innovativo di gestione delle informazioni digitali che contribuirà a sfruttare questi preziosi set di dati privati. Combinerà due tecnologie di gestione delle informazioni digitali emergenti, l’apprendimento automatico federato e la blockchain, per articolare una progettazione federata avanzata dell’apprendimento che preserva la privacy e in cui lo scambio di dati e modelli di formazione non sarà compromesso. Analizzerà anche i potenziali benefici dell’innovativa gestione delle informazioni digitali attraverso casi di ricerca ATM relativi al modello prognostico di bilanciamento della capacità della domanda avanzato del gestore di rete, integrato con dati operativi reali provenienti dagli utenti dello spazio aereo.
Obiettivo
This project proposes an innovative Digital Information Management (DIM) concept, i.e. the AICHAIN solution, that aims at enabling the cyber-secured exploitation of large private data sets that belong to different stakeholders and that contain valuable information for ATM operations. To overcome the stakeholders’ reluctance to share sensitive data, the exploitation will not be performed by exchanging the data itself but by articulating an advanced privacy-preserving federated learning architecture in which neither the training data nor the training model need to be exposed. This will be possible thanks to the innovative combination of two emerging DIM technologies: Federated Machine Learning (FedML) and Blockchain technologies.
The potential benefits of the new proposed DIM concept will be explored through ATM research use cases related to advanced Demand Capacity Balancing (DCB) predictive models of the Network Manager (NM), whose prediction performance is expected to significantly improve thanks to the exploitation of relevant operational private data from Airspace Users. The accuracy of the new DCB predictive models augmented with real operational data accessed through the AICHAIN solution will be benchmarked against the machine learning models for DCB that are currently in use or under research by NM.
The project will also address the exploration of governance and incentives mechanisms as part of the AICHAIN solution concept architecture, to facilitate the adoption of the concept and the alignment of interests of the key stakeholders (especially of the data owners). The design of advanced governance & incentives mechanisms, which could be implemented using the mechanism of “smart contracts” available in the toolset of Blockchain, will be complemented with a theoretical identification of data exploitation benefits and with discussions in workshops participated by external experts.
Campo scientifico
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
08005 Barcelona
Spagna