Artificial intelligence-based threat prediction system and method for cbrn
AssigneeAgency for Defense Development
InventorsHyunwoo NAM, Minjae KANG, Jungjae SON, Byungheon LEE
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Abstract
An object of the present invention is to provide a system and a method for predicting Chemical, Biological, Radiological and Nuclear (CBRN) threatsj, which are more realistic and reliable by correcting actual sensor data measured in a given zone when a CBRN situation occurs or pollution diffusion and transfer and diffusion data for each time zone acquired by using a pollution diffusion prediction tool.
Claims17
An artificial intelligence-based threat prediction system for Chemical, Biological, Radiological and Nuclear (CBRN) threats, comprising:
- an input information acquisition unit acquiring model input information for a CBRN pollution of indoor and outdoor spaces to be modeled;
- a pollution concentration data acquisition unit acquiring time zone-wise pollution concentration data of the indoor and outdoor spaces;
- and
- a high-fidelity pollution diffusion prediction modeling unit correcting the time zone-wise pollution concentration data of the indoor space by using artificial intelligence technology based on the model input information and the pollution concentration data, and calculating a pollution concentration for each lattice that partitions the indoor space.
An artificial intelligence-based threat prediction system for Chemical, Biological, Radiological and Nuclear (CBRN) threats, comprising:
- (a) acquiring, by an input information acquisition unit, model input information for a CBRN pollution in indoor and outdoor spaces to be modeled;
- (b) acquiring, by a pollution concentration data acquisition unit, time zone-wise pollution concentration data in the indoor and outdoor spaces;
- and
- (c) correcting, by a high-fidelity pollution diffusion prediction modeling unit, the time zone-wise pollution concentration data of the indoor space by using artificial intelligence technology based on the model input information and the pollution concentration data, and calculating a pollution concentration for each lattice that partitions the indoor space.
Dependencies are inferred from the claim text.