Connected Airspace Intelligence

ATM-EXCITE delivers new solutions for safe air traffic management and data exchange between civil and military aviation. The project responds to growing demand for digitalisation, security and coordination across European airspace.

UpVision contributes to the development of secure data transfer and validation in the ATM environment, enabling reliable cooperation between different types of air operations — from commercial flights to sensitive military missions.

Uspace4UAM prepares European cities for a future where drones and flying taxis are a routine part of transport. The project focuses on the safe deployment of Urban Air Mobility (UAM) into day-to-day operations and lays the groundwork for new transport services beyond urban environments.

UpVision participates in testing and validation of advanced drone delivery and U-space solutions, demonstrated for the first time in the Czech Republic over a 10 km distance with coordination from Air Traffic Control. As a future USSP, UpVision and project partners demonstrated safe drone operations in urban environments, including real flight scenarios and integration with existing ATM.

The project links development, regulation and real-world deployment — accelerating the shift from experiments to commercially viable services such as drone delivery and Urban Air Mobility.

MEDuSA brings an innovative approach to airspace protection using satellite technology. The project focuses on drone detection and tracking based on sensors monitoring GNSS communication within a defined perimeter — without the need for traditional radar or camera systems.

The solution targets a new way to monitor defined airspace volumes — from critical infrastructure to urban environments and public events.

The project focuses on the safe rollout of U-space airspace in the Czech Republic — defining operational procedures, technical parameters and gaining hands-on experience from the implementation of U-space services.

It targets organisations and institutions involved in managing uncrewed traffic, and environments with growing drone density, including advanced operations such as BVLOS.

The project develops an advanced control system and demonstrator for processing image and sensor data from swarms of unmanned aerial vehicles (UAVs). It uses AI and machine learning for real-time detection, classification and localisation of objects.

The solution targets applications that require coordinated multi-drone deployment and efficient processing of large volumes of data — for example in security, monitoring or crisis management.