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The Importance of a System-Level Approach When Bringing in New Technologies in Avionics
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Saab Surveillance, Saab Ab, Huskvarna, Sweden.
Saab Aeronautics, Saab Ab, Järfälla, Sweden.
2024 (English)In: AIAA/IEEE Digital Avionics Systems Conference - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2024Conference paper, Published paper (Refereed)
Abstract [en]

In the era of multiple industry trends and new technologies, avionics systems can benefit from several innovations. The complexity of modern electronics is increasing quickly and is being introduced as never before in new applications. At the algorithm level, the use of deep neural networks helps to solve problems that were never believed to be doable before. At the architecture level, hardware artificial intelligence accelerators, embedded graphical processing units, embedded sensors, etc., make it possible to create very powerful new functions. The list of new technologies is long. Besides technical challenges, system integrity and availability must be assured when integrating these new technologies into avionics functions. In this paper, we present emerging technologies and why a system-level approach is necessary when implementing these technologies. We also introduce supporting means for design assurance and fault-tolerance techniques. We illustrate the importance of a system-level approach through an example. Our example shows that when developing functions with new technologies and fault-tolerant architectures, the system safety assessment process is crucial for properly implementing a fail-safe design. It is also challenging due to potentially new failure modes.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024.
Series
AIAA/IEEE Digital Avionics Systems Conference - Proceedings, ISSN 21557195
Keywords [en]
machine learning, new technology, safety assessment, system safety, Deep neural networks, Failure modes, Fault tolerance, Outages, Algorithm-level, Avionic systems, Industry trends, Machine-learning, Neural-networks, New applications, Safety assessments, System-level approach, Graphics processing unit
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-69644DOI: 10.1109/DASC62030.2024.10749347ISI: 001453360400154Scopus ID: 2-s2.0-85211204702ISBN: 9798350349610 (print)OAI: oai:DiVA.org:mdh-69644DiVA, id: diva2:1922329
Conference
43rd AIAA DATC/IEEE Digital Avionics Systems Conference, DASC 2024, San Diego, USA, 29/9-3/10, 2024
Available from: 2024-12-18 Created: 2024-12-18 Last updated: 2025-10-10Bibliographically approved

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Forsberg, Håkan

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