| dc.contributor.author | Sen, Sagar | |
| dc.contributor.author | Husom, Erik Johannes | |
| dc.contributor.author | Goknil, Arda | |
| dc.contributor.author | Tverdal, Simeon | |
| dc.contributor.author | Nguyen, Phu Hong | |
| dc.date.accessioned | 2024-04-29T13:09:06Z | |
| dc.date.available | 2024-04-29T13:09:06Z | |
| dc.date.created | 2023-12-22T14:54:42Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | IEEE Software. 2023, 41 (2), 77-87. | en_US |
| dc.identifier.issn | 0740-7459 | |
| dc.identifier.uri | https://hdl.handle.net/11250/3128456 | |
| dc.description.abstract | We present a data pipeline to train and deploy uncertainty-aware virtual sensors in cyber-physical systems. Our virtual sensor predicts the expected values of a physical sensor and a standard deviation indicating the degree of uncertainty in its predictions. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.title | Uncertainty-aware Virtual Sensors for Cyber-Physical Systems | en_US |
| dc.type | Peer reviewed | en_US |
| dc.type | Journal article | en_US |
| dc.description.version | acceptedVersion | en_US |
| dc.rights.holder | © 2023 The authors/SINTEF | en_US |
| dc.source.pagenumber | 77-87 | en_US |
| dc.source.volume | 41 | en_US |
| dc.source.journal | IEEE Software | en_US |
| dc.source.issue | 2 | en_US |
| dc.identifier.doi | https://doi.org/10.1109/MS.2023.3306873 | |
| dc.identifier.cristin | 2217323 | |
| dc.relation.project | EC/H2020/958363 | en_US |
| dc.relation.project | EC/H2020/958357 | en_US |
| cristin.ispublished | true | |
| cristin.fulltext | postprint | |
| cristin.qualitycode | 2 | |
