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TRUSTWORTHY INTELLIGENT SYSTEM FOR REMOTE DIGITAL TOWER

Project description

Trustworthy and transparent AI for remote digital towers

Remote digital towers (RDTs), an innovative solution for enhancing data management at airports, are increasingly being adopted by airports worldwide to enhance safety and efficiency. Nevertheless, the substantial volume of generated data demands significant effort and attention for effective utilisation and organisation. The EU-funded TRUSTY project aims to enhance RDTs by leveraging artificial intelligence (AI) to boost their efficiency, data capacity and overall durability. Additionally, it aims to ensure higher levels of transparency and trustworthiness in their AI systems. To accomplish these objectives, the project will harness innovative interactive data visualisation discoveries, recent technologies and information visualisation techniques.

Objective

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.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-JU-RIA - HORIZON JU Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-SESAR-2022-DES-ER-01

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Coordinator

MALARDALENS UNIVERSITET
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 386 967,50
Address
UNIVERSITETSPLAN 1
722 20 VASTERAAS
Sweden

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Region
Östra Sverige Östra Mellansverige Västmanlands län
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 386 967,50

Participants (3)

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