Artificial Intelligence at the Edge in the Blockchain of Things

dc.contributor.authorTuan Nguyen Gia
dc.contributor.authorAnum Nawaz
dc.contributor.authorJorge Peña Queralta
dc.contributor.authorHannu Tenhunen
dc.contributor.authorTomi Westerlund
dc.contributor.organizationfi=sulautettu elektroniikka|en=Embedded Electronics|
dc.contributor.organizationfi=tietotekniikan laitos|en=Department of Computing|
dc.contributor.organization-code1.2.246.10.2458963.20.20754768032
dc.contributor.organization-code1.2.246.10.2458963.20.85312822902
dc.contributor.organization-code2606802
dc.converis.publication-id44657532
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/44657532
dc.date.accessioned2022-10-28T14:12:36Z
dc.date.available2022-10-28T14:12:36Z
dc.description.abstract<p>Traditional cloud-centric architectures for Internet-of-Things applications are being replaced by distributed approaches. The Edge and Fog computing paradigms crystallize the concept of moving computation towards the edge of the network, closer to where the data originates. This has important benefits in terms of energy efficiency, network load optimization and latency control. The combination of these paradigms with embedded artificial intelligence in edge devices, or Edge AI, enables further improvements. In turn, the development of blockchain technology and distributed architectures for peer-to-peer communication and trade allows for higher levels of security. This can have a significant impact on data-sensitive and mission-critical applications in the IoT. In this paper, we discuss the potential of an Edge AI capable system architecture for the Blockchain of Things. We show how this architecture can be utilized in health monitoring applications. Furthermore, by analyzing raw data directly at the edge layer, we inherently avoid the possibility of breaches of sensitive information, as raw data is never stored nor transferred outside of the local network<br /></p>
dc.format.pagerange267
dc.format.pagerange280
dc.identifier.eisbn978-3-030-49289-2
dc.identifier.isbn978-3-030-49288-5
dc.identifier.issn1867-8211
dc.identifier.jour-issn1867-8211
dc.identifier.olddbid186920
dc.identifier.oldhandle10024/170014
dc.identifier.urihttps://www.utupub.fi/handle/11111/41090
dc.identifier.urnURN:NBN:fi-fe2021042825598
dc.language.isoen
dc.okm.affiliatedauthorNguyen, Tuan
dc.okm.affiliatedauthorPeña Queralta, Jorge
dc.okm.affiliatedauthorTenhunen, Hannu
dc.okm.affiliatedauthorWesterlund, Tomi
dc.okm.affiliatedauthorNawaz, Anum
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline213 Electronic, automation and communications engineering, electronicsen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline213 Sähkö-, automaatio- ja tietoliikennetekniikka, elektroniikkafi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryGermanyen_GB
dc.publisher.countrySaksafi_FI
dc.publisher.country-codeDE
dc.relation.conferenceInternational Conference on Wireless Mobile Communication and Healthcare
dc.relation.doi10.1007/978-3-030-49289-2_21
dc.relation.ispartofjournalLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
dc.relation.volume320
dc.source.identifierhttps://www.utupub.fi/handle/10024/170014
dc.titleArtificial Intelligence at the Edge in the Blockchain of Things
dc.title.bookWireless Mobile Communication and Healthcare: 8th EAI International Conference, MobiHealth 2019, Dublin, Ireland, November 14-15, 2019, Proceedings
dc.year.issued2020

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