Descrizione del progetto
Un’IA affidabile e trasparente per torri digitali remote
Le torri digitali remote, una soluzione innovativa per migliorare la gestione aeroportuale dei dati, sono sempre più adottate dagli aeroporti di tutto il mondo per migliorare la sicurezza e l’efficienza. L’ingente volume di dati generati richiede tuttavia notevoli sforzi e attenzione affinché sia possibile garantire efficacia nel loro utilizzo e nella relativa organizzazione. Il progetto TRUSTY, finanziato dall’UE, si propone di migliorare le torri digitali remote sfruttando l’intelligenza artificiale (IA) per aumentarne l’efficienza, la capacità di dati e la durata complessiva. Inoltre, il progetto mira a garantire livelli più elevati di trasparenza e affidabilità nei propri sistemi di IA. Per raggiungere questi obiettivi, il progetto sfrutterà innovative scoperte per quanto riguarda la visualizzazione interattiva dei dati, tecnologie di recente sviluppo e varie tecniche di visualizzazione delle informazioni.
Obiettivo
Remote digital towers (RDT) are taking place around the world to ensure efficiency and safety. TRUSTY harnesses the power of artificial intelligence (AI) to enhance resilience, capacity, and efficiency in making significant advancements in the deployment of digital towers. The overall goal of TRUSTY is to provide adaptation in the level of transparency and explanation to enhance the trustworthiness of AI-powered decisions in the context of RDT. Through the video transmission data from RDT, TRUSTY considers the following major tasks:
1. Taxiway monitoring (i.e. bird hazard, presence of a drone, autonomous vehicle monitoring, human intrusion, etc.).
2. Runway monitoring (approach and landing) misalignment warning and the corresponding explanation.
To deliver trustworthiness in an AI-powered intelligent system several approaches are considered:
• ‘Self-explainable and Self-learning’ system for critical decision-making
• ‘Transparent ML’ models incorporating interpretability, fairness, and accountability
• ‘Interactive data visualization and HMI dashboard’ for smart and efficient decision support
• ‘Adaptive level of explanation’ regarding the user's cognitive state.
• “Human-centric AI” enhances the trustworthiness of AI-powered systems.
• “Human-AI teaming” to consider users’ feedback to insure some computation flexibility and the users’ acceptability.
To achieve the goal, TRUSTY will rely on the SotA developments in interactive data visualization, and user-centric explanation and on recent technological improvements in accuracy, robustness, interpretability, fairness, and accountability. We will apply information visualization techniques like visual analytics, data-driven storytelling, and immersive analytics in human-machine interactions (HMI). Thus, this project is at the crossroad of trustworthy AI, multi-model machine learning, active learning, and UX for human and AI model interaction.
Campo scientifico
- engineering and technologymechanical engineeringvehicle engineeringautomotive engineeringautonomous vehicles
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robotsdrones
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- social scienceseducational sciencespedagogyactive learning
Programma(i)
- HORIZON.2.5 - Climate, Energy and Mobility Main Programme
Argomento(i)
Meccanismo di finanziamento
HORIZON-JU-RIA - HORIZON JU Research and Innovation ActionsCoordinatore
722 20 VASTERAAS
Svezia