dc.contributor.author | Navakauskas, Dalius | |
dc.contributor.author | Kazlauskas, Mantas | |
dc.date.accessioned | 2023-12-22T07:07:18Z | |
dc.date.available | 2023-12-22T07:07:18Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 0868-4952 | |
dc.identifier.other | (crossref_id)153132833 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/xmlui/handle/123456789/153837 | |
dc.description.abstract | Healthcare has seen many advances in sensor technology, but with recent improvements in networks and the addition of the Internet of Things, it is even more promising. Current solutions to managing healthcare data with cloud computing may be unreliable at the most critical moments. High response latency, large volumes of data, and security are the main issues of this approach. The promising solution is fog computing, which offers an immediate response resistant to disconnections and ways to process big data using real-time analytics and artificial intelligence (AI). However, fog computing has not yet matured and there are still many challenges. This article presents for a computer scientist a systematic review of the literature on fog computing in healthcare. Articles published in six years are analysed from the service, software, hardware, information technologies and mobility with autonomy perspectives. The contribution of this study includes an analysis of recent trends, focus areas and benefits of the use of AI techniques in fog computing e-health applications. | eng |
dc.format | PDF | |
dc.format.extent | p. 577-602 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Scopus | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.source.uri | https://informatica.vu.lt/journal/INFORMATICA/article/1306/text | |
dc.title | Fog computing in healthcare: Systematic review | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.accessRights | Open access article under the CC BY license. | |
dcterms.license | Creative Commons – Attribution – 4.0 International | |
dcterms.references | 112 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Elektronikos fakultetas / Faculty of Electronics | |
dc.subject.researchfield | T 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.vgtuprioritizedfields | IK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems | |
dc.subject.ltspecializations | L105 - Sveikatos technologijos ir biotechnologijos / Health technologies and biotechnologies | |
dc.subject.en | fog computing | |
dc.subject.en | internet of things | |
dc.subject.en | healthcare | |
dc.subject.en | systematic review | |
dcterms.sourcetitle | Informatica | |
dc.description.issue | iss. 3 | |
dc.description.volume | vol. 34 | |
dc.publisher.name | Vilnius University | |
dc.publisher.city | Vilnius | |
dc.identifier.doi | 153132833 | |
dc.identifier.doi | 2-s2.0-85174199562 | |
dc.identifier.doi | 85174199562 | |
dc.identifier.doi | 1 | |
dc.identifier.doi | 001086306600006 | |
dc.identifier.doi | 10.15388/23-INFOR525 | |
dc.identifier.elaba | 179889127 | |