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Der in dieser Arbeit vorgestellte SECAI (<jats:italic>S<\/jats:italic>ustainable heating through <jats:italic>E<\/jats:italic>dge-<jats:italic>C<\/jats:italic>loud-based <jats:italic>A<\/jats:italic>rtificial <jats:italic>I<\/jats:italic>ntelligence Systems)-Ansatz verfolgt das Ziel, die Heizungssteuerung in Mehrfamilienh\u00e4usern und damit den CO<jats:sub>2<\/jats:sub>-Verbrauch durch den Einsatz von Informationstechnologien zu reduzieren.<\/jats:p><jats:p>Der SECAI-Ansatz betrachtet dabei das gesamte \u00d6kosystem bestehend aus Sensoren, Einzelraumregelungen, Zentralheizung, Mietenden und Vermietenden. Dabei wird der Heizbedarf von Privatwohnungen KI-basiert analysiert, um darauf aufbauend optimierte und abgestimmte Heizpl\u00e4ne f\u00fcr Geb\u00e4udekomplexe und Wohnungen zu erstellen, die in der Lage sind, durch Edge-Cloud-Technologien, Sensorik und Federated Learning ad hoc und datenschutzkonform auf \u00c4nderungen im Nutzungsverhalten zu reagieren. Diese Informationen werden zudem f\u00fcr die KI-basierte Steuerung der zentralen Heizanlagen im Geb\u00e4ude verwendet, in denen W\u00e4rme und Warmwasser f\u00fcr alle Wohnungen erzeugt wird. Hierf\u00fcr betrachtet SECAI vier Ebenen. Diese reichen von Sensoren und Aktoren (Nano), \u00fcber die Wohnung (Mikro) und das Geb\u00e4ude (Meso) bis zu Geb\u00e4udekomplexen und gleicharten Geb\u00e4uden (Makro) und stehen bei der Beheizung in starker Abh\u00e4ngigkeit zueinander. Rund um die SECAI-L\u00f6sung entsteht dabei ein komplexes \u00d6kosystem in dem Mietende, die Wohnungswirtschaft, Heizungshersteller und Anbieter von IoT-L\u00f6sungen mit Produkten und Diensten in Interaktion treten.<\/jats:p>","DOI":"10.1365\/s40702-023-00988-8","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T08:02:09Z","timestamp":1686816129000},"page":"850-871","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["SECAI\u00a0\u2013 Sustainable Heating through Edge-Cloud-based AI Systems"],"prefix":"10.1365","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1089-711X","authenticated-orcid":false,"given":"Henrik","family":"Kortum","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Hagen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1516-5129","authenticated-orcid":false,"given":"Marian","family":"Eleks","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8531-3273","authenticated-orcid":false,"given":"Jonas","family":"Rebstadt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Florian","family":"Remark","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0467-059X","authenticated-orcid":false,"given":"Maximilian","family":"Lowin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9725-0078","authenticated-orcid":false,"given":"Cristina Mihale","family":"Wilson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Birgid","family":"Eberhardt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andree","family":"Ro\u00df","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dominik","family":"Maih\u00f6fner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oliver","family":"Hinz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oliver","family":"Thomas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"93","published-online":{"date-parts":[[2023,6,15]]},"reference":[{"key":"988_CR1","doi-asserted-by":"publisher","first-page":"103445","DOI":"10.1016\/j.scs.2021.103445","volume":"76","author":"K Alanne","year":"2022","unstructured":"Alanne\u00a0K, Sierla\u00a0S (2022) An overview of machine learning applications for smart buildings. 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