Open AccessArtificial Neural Networks for Airport Runway Safety Systems
Author(s) -
D.E. Bekasov
Publication year - 2020
Publication title -
annals of disaster risk sciences
Language(s) - English
Resource type - Journals
eISSN - 2623-8934
pISSN - 2584-4873
DOI - 10.51381/adrs.v3i1.49
Subject(s) - runway , takeoff , architecture , artificial neural network , computer science , trajectory , asde x , takeoff and landing , real time computing , artificial intelligence , engineering , automotive engineering , aerospace engineering , physics , archaeology , astronomy , art , visual arts , history
This paper presents the analysis of the existing approaches to ensuring the safety of aircraft`s takeoff and landing at airport runways using video surveillance systems. The subject area is formalized, and security threats and measures to prevent them are assessed. Optional architecture of the system designed for detection and classification of moving objects in the airport runway area is presented. The architecture is based on Neural Networks with AI elements. Also the original method of runway objects’ trajectory tracking is proposed. And finally, the research results of the applicability of the proposed architecture are presented.