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Functional Requirements and Recommendations for AI-based Sustainable Energy Solutions

dc.contributor.authorLowin, Maximilian
dc.contributor.authorMihale-Wilson, Cristina
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorGergeleit, Martin
dc.contributor.editorMartin, Ludger
dc.date.accessioned2024-10-21T18:24:15Z
dc.date.available2024-10-21T18:24:15Z
dc.date.issued2024
dc.description.abstractSMEs contribute to energy conservation by innovating smart services across domains. This article supports the design and implementation of AI-based products and services for sustainable energy solutions by uniting insights from research and practice. Specifically, it presents an iterative approach to document and refine appropriate functional requirements from the literature and three expert focus groups. The set of requirements presented can help SMEs to allocate their development resources efficiently by indicating those functions that are a must or rather optional. Besides, to bolster SME initiatives for AI-based sustainable energy solutions, this article articulates several recommendations for implementing the most important requirements into practice.en
dc.identifier.doi10.18420/inf2024_148
dc.identifier.isbn978-3-88579-746-3
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45123
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-352
dc.subjectAI-based Services
dc.subjectFunctional Requirements
dc.subjectSustainable Energy Consumption
dc.subjectSustainable Heating
dc.titleFunctional Requirements and Recommendations for AI-based Sustainable Energy Solutionsen
dc.typeText/Conference Paper
gi.citation.endPage1716
gi.citation.publisherPlaceBonn
gi.citation.startPage1705
gi.conference.date24.-26. September 2024
gi.conference.locationWiesbaden
gi.conference.sessiontitleKünstliche Intelligenz im Mittelstand / KI-KMU2024

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