Artificial Intelligence-Based Assistance Systems for Environmental Sustainability in Smart Homes: A Systematic Literature Review on Requirements and Future Directions
dc.contributor.author | Brîncoveanu, Constantin | |
dc.contributor.author | Carl, K. Valerie | |
dc.contributor.author | Binz, Simon | |
dc.contributor.author | Weiher, Moritz-Andre | |
dc.contributor.author | Thomas, Oliver | |
dc.contributor.author | Hinz, Oliver | |
dc.contributor.editor | Klein, Maike | |
dc.contributor.editor | Krupka, Daniel | |
dc.contributor.editor | Winter, Cornelia | |
dc.contributor.editor | Gergeleit, Martin | |
dc.contributor.editor | Martin, Ludger | |
dc.date.accessioned | 2024-10-21T18:24:12Z | |
dc.date.available | 2024-10-21T18:24:12Z | |
dc.date.issued | 2024 | |
dc.description.abstract | Artificial Intelligence (AI) is increasingly being utilized to promote sustainable behavior, particularly in the context of smart homes. Such solutions can significantly enhance resource consumption sustainability by leveraging data analysis for ecological benefits. This systematic literature review examines the requirements for data-driven AI applications aimed at improving environmental sustainability in smart homes, based on an analysis of 60 selected papers. Key findings include the importance of predictive analytics, privacy and security, context-aware features, real-time monitoring, interoperability, efficiency strategies, personalized user engagement, user interface design, and behavioral aspects. We highlight technological advancements that facilitate more comprehensive applications and identify the need for integrating diverse features to build consumer trust and acceptance. This review provides an overview of current smart home technologies and suggests future research directions to enhance energy efficiency, user comfort, and environmental sustainability. | en |
dc.identifier.doi | 10.18420/inf2024_103 | |
dc.identifier.isbn | 978-3-88579-746-3 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/45074 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | INFORMATIK 2024 | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-352 | |
dc.subject | Smart Home | |
dc.subject | Artificial Intelligence-Based Assistance Systems | |
dc.subject | Data-Driven Assistance | |
dc.subject | Environmental Sustainability | |
dc.subject | Energy Efficiency | |
dc.subject | Grounded Theory Literature Reviews | |
dc.title | Artificial Intelligence-Based Assistance Systems for Environmental Sustainability in Smart Homes: A Systematic Literature Review on Requirements and Future Directions | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 1182 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 1165 | |
gi.conference.date | 24.-26. September 2024 | |
gi.conference.location | Wiesbaden | |
gi.conference.sessiontitle | 5. Workshop "KI in der Umweltinformatik" (KIU-2024) |
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