NOTAMs are time- and safety-critical announcements of temporary changes to global flight conditions essential to personnel concerned with flight operations. In this paper we introduce SemNOTAM, a knowledge-based framework that enables fine-grained intelligent semantic filtering and provides a formal, explicit, and machine-readable representation of Digital NOTAMs and associated business rules. Filtering functionalities for time, space, aircraft, user-defined aspects, and any combination thereof are supported. Furthermore, SemNOTAM is designed in such a way that it can be employed in various scenarios, e.g., On-Board briefing or Flight Planning Briefing. Regardless the specific scenario 100% recall is supported.


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    Titel :

    AIRM-based, fine-grained semantic filtering of notices to airmen


    Beteiligte:


    Erscheinungsdatum :

    2015-04-01


    Format / Umfang :

    349355 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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