Australian defence ministry selects DroneShield’s AI technology, expands C-UAS and sensor fusion capabilities

The Australian Ministry for Defence has selected DroneShield for a Phase 2 (prototyping) Defence Innovation Hub Contract, as part of a AUD10 million Artificial Intelligence grant round to strengthen Australia’s military capability and support highly skilled jobs in the country’s defence industry.

DroneShield will examine autonomous AI-enabled computer-vision search, track and classification techniques with a focus on multi-sensor fusion, beyond traditional sensor “correlation”.  The combination of advanced computer-vision and sensor fusion allows automatic generation of target data for future use – an essential part of the Intelligence Mission Data (IMD) cycle for defence, Government agency and similar customers.

The project is valued at approximately AUD800,000, and leverages two core elements of DroneShield’s technology base: Artificial Intelligence/Machine Learning (AI) in the Computer Vision space, and the Command-and-Control (C2) system.

DroneShield will examine autonomous AI-enabled computer-vision search, track and classification techniques with a focus on multi-sensor fusion, beyond traditional sensor “correlation”.   The combination of advanced computer-vision and sensor fusion allows automatic generation of target data for future use – an essential part of the Intelligence Mission Data (“IMD”) cycle for defence, government agency and similar customers.

This technology stream has direct application in both the C-UAS space as well as military/government agency applications.

Oleg Vornik, DroneShield’s CEO said: “We have a deep history of collaboration with the Australian military, including presently delivering a AUD3.8 million Electronic Warfare project, and this initial Defence Innovation Hub grant opens a new teaming sovereign industrial capability front.”

(Image: DroneShield computer-vision screenshot)

For more information visit:

www.droneshield.com

Share this:
D-Fend advert. Click for website