TRUSTY: TRUSTWORTHY INTELLIGENT SYSTEM FOR REMOTE DIGITAL TOWER
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Overall, the goal of TRUSTY is to provide adaptation in the level of transparency to enhance the trustworthiness of AI-powered decisions in the context of remote digital towers (RDTs). While in an actual tower, operators have direct visual access to the taxiway and runway monitoring, the RDTs concept only provides such information through video transmission with a warning and the corresponding explanation. To deliver trustworthiness in an AI-powered intelligent system TRUSTY will consider several approaches, and they are listed:
• ‘Self-explainable and Self-learning’ system for critical decision-making
• ‘Transparent ML’ models incorporating interpretability, fairness, and accountability
• ‘Interactive data visualization and multimodal human-machine interface/interactions (HMI), i.e., Graphical User Interface (GUI)’ for smart and efficient decision support
• ‘Adaptive level of explanation’ regarding the user's cognitive state.
• “HCAI” to enhance the trustworthiness of AI-powered systems.
• “Human-machine collaboration (HMC) or Human-AI teaming (HAIT)” to consider user feedback to insure some computation flexibility and the users’ acceptability.
| First Name | Last Name | Title |
|---|---|---|
| Mobyen Uddin | Ahmed | Professor |
| Shahina | Begum | Professor |
| Shaibal | Barua | Senior Lecturer |
| Mir Riyanul | Islam | Post Doc |
Enhancing Industrial AI Usability Through Human-AI Interaction (Jul 2026) Marcus Hammarström , Liam Burberry Gahm , Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum, Emmanuel Weiten , Daniel Aurel 28th International Conference on Computer and Information Technology (ICCIT25)
An End-to-End Explainable Fault Prediction Pipeline for Embedded Test Systems (Jul 2026) Md Motaher Hossain Bhuiyan, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum 28th International Conference on Computer and Information Technology (ICCIT25)
Bias-Aware Generative XAI for Sustainable Air Traffic Control: A Methodological Framework with Predictive Telemetry (Jun 2026) Mobyen Uddin Ahmed, Christophe Hurter , Shaibal Barua, Shahina Begum, Pietro Aricò , Nicola Cavagnetto International Conference on Artificial Intelligence, Automation and Control Technologies (AIACT 2026)
Explainable Quantum Machine Learning Concepts for Trajectory Optimization in Air Traffic Management (May 2026) Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed, Henri de Boutray , Christophe Hurter International Conference on Modern Artificial Intelligence and Data Science Systems (MAIDSS26)
Quantum Machine Learning for Optimisation: A Domain Focused Survey (May 2026) Surya Teja Darbhamalla, Shahina Begum, Shaibal Barua, Mobyen Uddin Ahmed International Conference on Modern Artificial Intelligence and Data Science Systems (MAIDSS26)
Challenges and Future Directions for AI-based Systems for Remote Digital Towers (May 2026) Mir Riyanul Islam, Alexandre Veyrie , Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Christophe Hurter , Pietro Aricò International Conference on Modern Artificial Intelligence and Data Science Systems (MAIDSS26)
| Partner | Type |
|---|---|
| ECOLE NATIONALE DE L AVIATION CIVILE | Academic |
| UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA | Academic |
| DEEP BLUE SRL | Industrial |
