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

F. Burgstaller, D. Steiner, M. Schrefl, E. Gringinger, S. Wilson, S. van der Stricht
Burg15a (2015)
2015 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".
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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.