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Deutsch Intern
    Chair of Computer Science VIII - Aerospace Information Technology

    SkyCAM-5

    SkyCAM-5 is a test platform for the autonomous detection of Unidentified Aerial Phenomena (UAP's). Through the use of image processing algorithms, the sky is continuously monitored for unusual phenomena. Current machine learning models are applied to reduce wrong detections. The main objective of the camera system is to detect UAP's. It can also detect short duration luminous phenomena such as lightning or meteors.  

    Detected objects on 15. December 2021 (helicopter, birds) by SkyCAM-5 (Photo: H. Kayal)

    Hinter SkyCAM-5 steht eine komplexe Software-Architektur. Hier der Client mit den Reports über die Beobachtungen und deren Klassifizierung.

    SkyCAM-5 (Photo: H. Kayal)

     

     

    Fig.: Functionality of the SkyCAM-5 software for the detection of unknown phenomena

    Known objects such as birds, insects or helicopters are often detected in the camera's environment. These are detected and filtered out by a Convolutional Neural Network. The system will be extended by a numbner of additional elements and features in the future such as multiply sensors, tracking system etc.

                                

    Fig.: Examples of detected objects