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AIRM-based, Fine-grained Semantic Filtering of Notices to Airmen

Authors: F. Burgstaller, D. Steiner, M. Schrefl, E. Gringinger, S. Wilson, S. van der Stricht
Paper: Burg15a (2015)
Citation: Integrated Communications, Navigation and Surveillance Conference (ICNS), April 21-23, 2015, Washington, USA, IEEE, IEEE Publ., pp. D3-1 - D3-13, 2015. Publication received "Best Student Paper Award".
Resources: Copy  (In order to obtain the copy please send an email with subject  Burg15a  to dke.win@jku.at)


Abstract (English): 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.