Design of a recommender system to improve the environmental impact of companies based on their material and energy balances
| dc.contributor.author | Fayed, Hatem | |
| dc.contributor.author | Wohlgemuth, Volker | |
| dc.contributor.editor | Wohlgemuth, Volker | |
| dc.contributor.editor | Kranzlmüller, Dieter | |
| dc.contributor.editor | Höb, Maximilian | |
| dc.date.accessioned | 2023-12-15T09:22:24Z | |
| dc.date.available | 2023-12-15T09:22:24Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | As worldwide agreements aiming to reduce the carbon footprint keep coming into effect, many companies aim to become more efficient in their production process. However, it is costly to hire environmental experts to help with the efficiency and carbon reduction process. This research aims to analyze the possibility of creating a Recommender System (RS) which suggests Carbon Reduction Measures (CRM) to the users based on their Life Cycle Assessment (LCA) reports. Based on the literature review into the latest RS techniques and the available databases, a study was conducted into creating a RS prototype. Analysis of the results demonstrates, that with the currently available databases, it is not possible to create an effective RS. The results indicate that in order to be able to create a functional and useful RS more detailed data needs to be extractable from the LCA tool. Further research is needed into the exports from other Environmental Management Information Systems (EMIS) and the identification of other factors that could strengthen the effectiveness of the RS. | en |
| dc.identifier.doi | 10.18420/env2023-017 | |
| dc.identifier.isbn | 978-3-88579-736-4 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/43337 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | EnviroInfo 2023 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-342 | |
| dc.subject | Artificial Intelligence; Resource and Energy Efficiency; Recommender System; Material and Energy Balance; LCA | |
| dc.title | Design of a recommender system to improve the environmental impact of companies based on their material and energy balances | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 194 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 187 | |
| gi.conference.date | 11.-13. Oktober 2023 | |
| gi.conference.location | Garching, Germany | |
| gi.conference.review | full | |
| gi.conference.sessiontitle | Environmental Impact Assessment and Optimization |
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