OP-TRACK-DXB: Operator tracking and load balancing for ATC operators with advanced AI

Purpose and goal

In the project, we have developed and evaluated an advanced prototype decision support system that uses eye tracking to evaluate air traffic controllers´ health and performance in real time. An algorithm to dynamically allocate appropriate flight sectors to the air traffic controller was developed by the team at the University of Sharjah. The joint group has presented the collaboration and shown the prototype during several visits to the UAE, including at EXPO2020 during Sweden week. The project has also resulted in a university spin-off - Cognible AI - which operates in related areas.

Expected results and effects

The evaluation of the prototype showed that DANS, GCAA and the Municipality of Dubai saw the prototype as particularly suitable for Air Traffic Management - for which it was designed - but also for other applications such as training and surveillance of drones in the "smart city" (for drone coordinators ). In addition to this, the project has led to participation in several national and international collaborations and project (WASP/WARA-PS, HAIKU, EXPLAIN, Saab Aeronautics/Brasilien, AI4REALNET) as well as some further development of our software framework SOMA-AI.

Planned approach and implementation

The travel ban and restrictions during the Covid pandemic made integration and evaluation difficult at Dubai Air Navigation Services (DANS), which was our industrial partner in the UAE. The problems were mitigated by us getting access to a simulator from the University of Delft before the first demonstration, and that equipment and servers were shipped to the University of Sharjah where the evaluation was done in the spring of 2023 with, among others, representatives from DANS.