In spacecraft operations, ensuring the spacecraft health is paramount for mission success and longevity. The health analysis involves meticulous examination of data, typically presented in the form of graphs and plots. This process demands substantial human effort and time investment, where analysts determine the spacecraft’s condition based on patterns observed in related parameters. However, this manual approach can be significantly enhanced through the integration of AIML algorithms. Here propose a novel framework for automated health analysis of spacecraft utilizing AIML techniques. By harnessing the power of artificial intelligence, our system aims to accelerate and streamline the spacecraft health assessment process.


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    Titel :

    Image Based Spacecraft Health Evaluation by AIML Based Expert System


    Beteiligte:
    Dai, Bijoy Kumar (Autor:in) / Paul, Debashish (Autor:in) / Priyanka (Autor:in) / Kiran, Gubbala (Autor:in) / Mv, Roopa (Autor:in) / Jackson, Leo (Autor:in) / Harinath, Nandini (Autor:in) / Ramakrishna, BN (Autor:in)


    Erscheinungsdatum :

    22.07.2024


    Format / Umfang :

    2765808 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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