UTM systems can be thought of as the required infrastructure that enables the incorporation of drones into airspace, allowing for the control, management and tracking of drones in the skies while ensuring compliance and safe operation.
This will facilitate adoption of drones across numerous sectors including private, economic and research. Thus, accelerating the deployment and development of drone systems.
Our distributed systems research focuses on creating resilient, scalable infrastructures for managing UAV traffic across wide geographical areas. We explore decentralized approaches that can maintain operational integrity even in the presence of network partitions or node failures.
Current research includes developing distributed ledger technologies for UTM, consensus algorithms for airspace allocation, and edge computing architectures that minimize latency for time-critical decisions in UAV traffic management.
Our research in security protocols focuses on developing robust communication and authentication mechanisms to ensure the integrity and confidentiality of UAV operations. We investigate novel cryptographic approaches tailored to the unique constraints of aerial vehicles, including limited computational resources and intermittent connectivity.
Current projects include the development of lightweight authentication protocols for UAV swarms, secure handover mechanisms for cross-domain UAV operations, and threat modeling for next-generation aerial communication networks.
Our AI research focuses on developing intelligent algorithms for coordinating multiple UAVs in shared airspace. We investigate machine learning approaches for trajectory prediction, anomaly detection, and dynamic resource allocation in UTM systems.
Current projects include reinforcement learning for collision avoidance, federated learning for privacy-preserving UAV coordination, and explainable AI for transparent decision-making in critical UTM operations.
We are exploring the use of eXtended Reality (XR) to develop innovative methods that will enhance how UAVs can be observed, managed, and controlled by the appointed authorities and departments.
We have proposed an XR system that will provide Law Enforcement Officers (LEOs) information in real-time for surveillance and monitoring of the drone ecosystem in their vicinity. Furthermore, we are working on integrating it with the open-source UTM backend by XTM alliance. By utilizing XR, users can interface with UTM services, providing a seamless and intelligent experience to intuitively understand the environment around them.
