Towards the Certification of an Evacuation Assistance System Utilizing AI-based Approaches
2024 (English)In: 2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops (ISSREW), Tsukuba, Japan: Institute of Electrical and Electronics Engineers (IEEE), 2024, p. 240-246Conference paper, Published paper (Refereed)
Abstract [en]
Using Artificial Intelligence-based approaches in safety-critical applications requires special attention during development. For instance, as of the beginning of 2027, European Union regulations mandate certification by a notified body for AI integration in safety-critical machinery applications. Nevertheless, AI-based approaches find application across diverse domains, enhancing system performance. Evacuation Assistance Systems used for evacuating buildings during emergencies like fires or terrorist attacks are examples in this context. In recent years, there has been a surge in research and standardization attempts to provide an assurance base for utilizing AI techniques in safety-critical applications from the technical and legislative perspectives. However, the focus is often reduced to automated driving and robotics, and many questions still need to be answered.This paper presents our research on the certification of AI-based systems. We highlight our effort in determining the relevant international standards that need to be complied with. The contribution of this paper is a certification concept for AI-based systems, where performance and reliability are crucial. The unique overview of state-of-the-art and industrial standards allows a certification attempt for this type of system. It also provides a base for future work beyond the scope of automated driving and robotics, such as assistance systems and building automation.The analytical discourse presented in this contribution justifies and highlights the mapping of standards and techniques to required functionalities and architectural components of the Evacuation Assistance System, supporting the quality and performance, system acceptance, and certification for the dedicated domain and purpose.
Place, publisher, year, edition, pages
Tsukuba, Japan: Institute of Electrical and Electronics Engineers (IEEE), 2024. p. 240-246
Series
IEEE International Symposium on Software Reliability Engineering Workshops, E-ISSN 2994-810X
Keywords [en]
Certification, Evacuation Assistance System, Artificial Intelligence, Machine Learning, Safety
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mau:diva-72840DOI: 10.1109/issrew63542.2024.00086ISI: 001462541600049Scopus ID: 2-s2.0-85215301641ISBN: 979-8-3503-6704-1 (electronic)OAI: oai:DiVA.org:mau-72840DiVA, id: diva2:1922944
Conference
2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops (ISSREW), Tsukuba, Japan, 28-31 October 2024
2024-12-192024-12-192025-08-14Bibliographically approved