Visualising Network Traffic Data From AirTraffic Control Radio Systems

Walker, Adam (2019) Visualising Network Traffic Data From AirTraffic Control Radio Systems. MRes thesis, University of Lincoln.

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Visualising Network Traffic Data From AirTraffic Control Radio Systems
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Item Type:Thesis (MRes)
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Abstract

In recent years the aviation industry has begun to embrace digital technology forAir Traffic Control (ATC) radio systems. This change has created challenges not onlyfor the industry but also for personnel. However, this implementation offers manyimprovements over older systems; more precise control, straightforward integrationwith other ATC systems and a more efficient way to provide software updates. Thechallenge for personnel is to develop a new skillset enabling a learning transitionfrom analogue to digital systems, with a specific emphasis on computer networkingskills.This project was undertaken in collaboration between the University of Lincoln(UoL) and Park Air Systems (PAS), an industry-leading provider of Air-Space com-munication solutions. A system has been developed to find a mechanism to monitorand visualise network traffic. The use of graphs provides a direct interface for theend-users, enabling a mechanism for identifying performance issues to meet thetransitional challenges from analogue to digital. An easy to use interface has beendesigned, which will enable non-technical users to interact effectively with the sys-tem.Considerable testing was undertaken to investigate the system usability concern-ing the practical application for users with limited networking experience. A surveyprovided a range of quantitative and qualitative data which was further analysed toscrutinize user perspectives on system usability. This involved engineers from PASand postgraduate students from UoL to compare results between direct industrypersonnel and unaffiliated participants.

Keywords:AirTraffic Control, Radio Systems
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:39937
Deposited On:24 Jan 2020 14:42

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