Semi-autonomous border surveillance platform combining next generation unmanned aerial vehicles with ultra-high-resolution multi-sensor surveillance payload
01.06.2020 - 30.11.2023
Related Solutions:Smart Exploitation of Data and Visual Analytics
BorderUAS will combine for the first time an airship (multi-role lighter-than-air unmanned aerial vehicle) with an ultra-high-resolution multi-sensor surveillance payload supporting border surveillance as well as search & rescue applications in areas with difficult terrain. The remote sensing payload will include a range of sensors: synthetic aperture radar (SAR), shortwave/longwave infrared (SWIR/LWIR), visible spectrum, hyperspectral and acoustic cameras; for both, direct target detection as well as indirect detection by vegetation disturbance analysis.
The project will develop central coordination of the ground units (command & control centre), innovative data models (to identify anomalous patterns and preferred routes) and advanced audio/video analytics and storage (to provide additional detection capabilities).
Vicomtech will contribute to the project with its expertise on surveillance systems, applying innovative machine learning solutions to the analysis of video, providing semantic analysis and fusion of security events captured by the multimodal variety of the implemented sensors, and employing data mining technologies for interactive, end-user tailored visual analytics of the captured data.
The consortium counts with 19 partners from 12 European countries, covering the technological, research, border control agency and NGO sectors.
The coordinator is Vicomtech (ES) and the partners are Hipersfera (HR), AVT (HR), DIAN (IT), DIRACS (SER),
ADITESS (CY), TUC (GR) , IMP(SER), SIMAVI (RO), KEMEA (GR), Hellenic Police (GR), CDBP of
Bulgaria (BG), IPTFT (RO), IGPF MAI (MD), SBGS of Ukraine (UKR), SBC of Belarus (BLR), Interakcia
(BLR), MITLA (MT), FORTH (GR)
Web site: https://borderuas.eu/
This project has received funding from the European Union’s Horizon 2020 research and innovation
programme under grant agreement No 883272
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