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Analysis of Potential Cognitive Computing Aided Tasks

Cockpit operations of large commercial aircraft such as the A350, A380 or A320, or similar, will be analysed along 2 directions: the pilot [“man in the loop”] interaction with the systems and the nature of information delivered. The analysis should allow for identifying specific in-flight conditions, related pilot behaviour, and how data is interpreted, and how and when collaborative / assisted decisions are made. This task will also devise initial case studies deemed relevant to extrapolate the potential of cognitive computing and to demonstrate how they will offer a significant aid to the pilot. The knowledge gained will help developing the initial concept for a digital assistant function supporting full or reduced flight crews.

State of the Art of cognitive computing algorithms

This deliverable will present a state of the art of cognitive computing applied in cockpit, healthcare and other relevant fields for the project. The state of the art will collect the most relevant papers and projects related to machine learning and artificial intelligence algorithms and the application of these alrogithms. This state of the art will set the basis for the project in order to explore the use cases and produce the roadmap that will be included in later deliverables.

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Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reports

Author(s): Néstor Jiménez-Campfens, Adrián Colomer, Javier Núñez, Juan M. Mogollón, Antonio L. Rodríguez, Valery Naranjo
Published in: Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II, Issue 12490, 2020, Page(s) 148-155
DOI: 10.1007/978-3-030-62365-4_14