dc.contributor.author | Kanapram, DT | en_US |
dc.contributor.author | Marchese, M | en_US |
dc.contributor.author | Bodanese, EL | en_US |
dc.contributor.author | Gomez, DM | en_US |
dc.contributor.author | Marcenaro, L | en_US |
dc.contributor.author | Regazzoni, C | en_US |
dc.date.accessioned | 2022-02-25T12:09:50Z | |
dc.date.issued | 2021 | en_US |
dc.identifier.issn | 2327-4662 | en_US |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/77025 | |
dc.format.extent | 3224 - 3241 | en_US |
dc.relation.ispartof | IEEE INTERNET OF THINGS JOURNAL | en_US |
dc.subject | Data models | en_US |
dc.subject | Task analysis | en_US |
dc.subject | Bayes methods | en_US |
dc.subject | Vehicle dynamics | en_US |
dc.subject | Sensors | en_US |
dc.subject | Internet of Things | en_US |
dc.subject | Hidden Markov models | en_US |
dc.subject | Abnormality detection | en_US |
dc.subject | collective awareness (CA) | en_US |
dc.subject | dynamic Bayesian network (DBN) | en_US |
dc.subject | Markov jump particle filter (MJPF) | en_US |
dc.subject | self-awareness (SA) | en_US |
dc.title | Dynamic Bayesian Collective Awareness Models for a Network of Ego-Things | en_US |
dc.type | Article | |
dc.rights.holder | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
dc.identifier.doi | 10.1109/JIOT.2020.3043199 | en_US |
pubs.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000621420700017&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
pubs.issue | 5 | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 8 | en_US |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |