Solution Overview The AI-Based Command Decision Support System, "KWM," identifies battlefield targets and recommends optimal weapon system combinations. It supports end-to-end "Sensor-to-Shooter" execution for rapid, accurate, and efficient engagement and command decision-making. Main Features Identifies targets on the battlefield using integrated sensors and data Recommends the most effective attack strategies for both reconnaissance and attack missions Provides command decision support through real-time analysis and visualization Suggests and allocates optimal target formations and strike assets Supports on-site command and control with a user-friendly interface Key Advantages Enables quick, accurate, and efficient engagement of enemy targets Automated recommendation of attack strategies and allocation of strike resources Real-time synchronization between reconnaissance and attack kill webs Direct connection from detection to strike (Sensor-to-Shooter capability) Increases operational efficiency and decision-making accuracy in complex battlefield environments Applied Cases Successfully piloted in the Army Tiger Boost Project in 2024 Used for command decision-making and efficient allocation of attack resources in live military scenarios

The DLR exhibit "Maritime Situation Image" at the Seoul ADEX 2025 uses a VR presentation to illustrate how the use of maritime situation images can be utilised for the protection of maritime infrastructures. Three subject areas are presented and explained: the ‘SeaCat’ autonomous underwater vehicle (AUV) concept on object detection in the underwater area, the topic muon tomography, i.e. the use of cosmic radiation (muons) for the tomographic examination of objects such as freight containers, and Distributed Acoustic Sensing (DAS) on the detection of ships and submerged objects using fibre optic cables on the seabed.

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