Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.3241
DC FieldValueLanguage
dc.contributor.authorCinar, Samet-
dc.contributor.authorÖnen, Senem-
dc.contributor.authorWieczorek, Nils-
dc.contributor.authorIhsanullah, Sohoo-
dc.contributor.authorKuchta, Kerstin-
dc.date.accessioned2021-01-13T15:30:42Z-
dc.date.available2021-01-13T15:30:42Z-
dc.date.issued2021-01-02-
dc.identifierdoi: 10.3390/pr9010085-
dc.identifier.citationProcesses 9 (1): 85 (2021)de_DE
dc.identifier.issn2227-9717de_DE
dc.identifier.urihttp://hdl.handle.net/11420/8420-
dc.description.abstractIn the biogas plants, organic material is converted to biogas under anaerobic conditions through physical and biochemical processes. From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process. In particular, the anaerobic digestion process, which consists of sequential complex biological reactions, requires improved monitoring to prevent inhibition. Conventional implemented methods at the biogas plants are not adequate for monitoring the operational parameters and finding the correlation between them. As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation. This review paper first examines the need for monitoring at the biogas plants with giving details about the process and process monitoring as well. In the following sections, the current situation of implementations of Artificial Intelligence in the biogas plant operation and in the similar industries will be represented. Moreover, considering that all the information gathered from literature and operational needs, an implementation model will be presented.-
dc.description.abstractIn the biogas plants, organic material is converted to biogas under anaerobic conditions through physical and biochemical processes. From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process. In particular, the anaerobic digestion process, which consists of sequential complex biological reactions, requires improved monitoring to prevent inhibition. Conventional implemented methods at the biogas plants are not adequate for monitoring the operational parameters and finding the correlation between them. As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation. This review paper first examines the need for monitoring at the biogas plants with giving details about the process and process monitoring as well. In the following sections, the current situation of implementations of Artificial Intelligence in the biogas plant operation and in the similar industries will be represented. Moreover, considering that all the information gathered from literature and operational needs, an implementation model will be presented.en
dc.language.isoende_DE
dc.publisherMultidisciplinary Digital Publishing Institutede_DE
dc.relation.ispartofProcessesde_DE
dc.rightsCC BY 4.0de_DE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/de_DE
dc.subject.ddc620: Ingenieurwissenschaftende_DE
dc.titleIntegration of artificial intelligence into biogas plant operationde_DE
dc.typeArticlede_DE
dc.date.updated2021-01-08T14:44:21Z-
dc.identifier.doi10.15480/882.3241-
dc.type.diniarticle-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.0120094-
tuhh.oai.showtruede_DE
tuhh.abstract.englishIn the biogas plants, organic material is converted to biogas under anaerobic conditions through physical and biochemical processes. From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process. In particular, the anaerobic digestion process, which consists of sequential complex biological reactions, requires improved monitoring to prevent inhibition. Conventional implemented methods at the biogas plants are not adequate for monitoring the operational parameters and finding the correlation between them. As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation. This review paper first examines the need for monitoring at the biogas plants with giving details about the process and process monitoring as well. In the following sections, the current situation of implementations of Artificial Intelligence in the biogas plant operation and in the similar industries will be represented. Moreover, considering that all the information gathered from literature and operational needs, an implementation model will be presented.de_DE
tuhh.publisher.doidoi: 10.3390/pr9010085-
tuhh.publication.instituteUmwelttechnik und Energiewirtschaft V-9de_DE
tuhh.identifier.doi10.15480/882.3241-
tuhh.type.opus(wissenschaftlicher) Artikel-
dc.type.driverarticle-
dc.type.casraiJournal Article-
tuhh.container.volume9de_DE
tuhh.container.startpage1de_DE
tuhh.container.endpage18de_DE
dc.rights.nationallicensefalsede_DE
tuhh.container.articlenumber85de_DE
local.status.inpressfalsede_DE
local.type.versionpublishedVersionde_DE
item.creatorGNDCinar, Samet-
item.creatorGNDÖnen, Senem-
item.creatorGNDWieczorek, Nils-
item.creatorGNDIhsanullah, Sohoo-
item.creatorGNDKuchta, Kerstin-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.creatorOrcidCinar, Samet-
item.creatorOrcidÖnen, Senem-
item.creatorOrcidWieczorek, Nils-
item.creatorOrcidIhsanullah, Sohoo-
item.creatorOrcidKuchta, Kerstin-
item.languageiso639-1en-
item.openairetypeArticle-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
crisitem.author.deptUmwelttechnik und Energiewirtschaft V-9-
crisitem.author.deptUmwelttechnik und Energiewirtschaft V-9-
crisitem.author.deptUmwelttechnik und Energiewirtschaft V-9-
crisitem.author.deptUmwelttechnik und Energiewirtschaft V-9-
crisitem.author.deptUmwelttechnik und Energiewirtschaft V-9-
crisitem.author.orcid0000-0001-9550-636X-
crisitem.author.orcid0000-0002-1921-4450-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
crisitem.author.parentorgStudiendekanat Verfahrenstechnik-
Appears in Collections:Publications with fulltext
Files in This Item:
File Description SizeFormat
processes-09-00085.pdf1,63 MBAdobe PDFThumbnail
View/Open
Show simple item record

Page view(s)

86
Last Week
9
Last month
checked on Jan 26, 2021

Download(s)

17
checked on Jan 26, 2021

Google ScholarTM

Check

Note about this record

Export

This item is licensed under a Creative Commons License Creative Commons