https://scholars.lib.ntu.edu.tw/handle/123456789/487815
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Huang, Z. | en_US |
dc.contributor.author | Lin, K.-J. | en_US |
dc.contributor.author | Tsai, B.-L. | en_US |
dc.contributor.author | Yan, S. | en_US |
dc.contributor.author | CHI-SHENG SHIH | en_US |
dc.creator | Huang, Z.;Lin, K.-J.;Tsai, B.-L.;Yan, S.;Shih, C.-S. | - |
dc.date.accessioned | 2020-05-04T07:44:11Z | - |
dc.date.available | 2020-05-04T07:44:11Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | https://scholars.lib.ntu.edu.tw/handle/123456789/487815 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044529670&doi=10.1016%2fj.future.2018.03.003&partnerID=40&md5=f426648c941963bf710f7bfddf72e23d | - |
dc.description.abstract | This paper presents the edge intelligence support for smart Internet of Things (IoT) using the service-oriented architecture. We propose an edge intelligence framework for building smart IoT applications. The proposed edge intelligence framework pushes the streaming processing capability from cloud core to edge devices, in order to better support timely and reliable streaming data analytics in smart IoT applications. We have designed annotation based programming primitives for developers to build online learning capabilities on edge devices. We have also implemented a user activity recognition engine, and compared its performances between running on either an edge device or cloud servers. Using our edge intelligence framework can improve the real-time and fault-tolerance performance significantly without degrading the activity recognition accuracy in a smart home. © 2018 Elsevier B.V. | - |
dc.relation.ispartof | Future Generation Computer Systems | - |
dc.subject.other | Automation; Fault tolerance; Information services; Intelligent buildings; Online systems; Pattern recognition; Service oriented architecture (SOA); Activity recognition; Edge intelligence; Fault tolerance performance; Internet of Things (IOT); IOT applications; Online activities; Service Oriented; Streaming processing; Internet of things | - |
dc.title | Building edge intelligence for online activity recognition in service-oriented IoT systems | en_US |
dc.type | journal article | en |
dc.identifier.doi | 10.1016/j.future.2018.03.003 | - |
dc.identifier.scopus | 2-s2.0-85044529670 | - |
dc.relation.pages | 557-567 | - |
dc.relation.journalvolume | 87 | - |
item.cerifentitytype | Publications | - |
item.fulltext | no fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | journal article | - |
item.grantfulltext | none | - |
crisitem.author.dept | Networking and Multimedia | - |
crisitem.author.dept | Computer Science and Information Engineering | - |
crisitem.author.dept | Intel-NTU Connected Context Computing Center | - |
crisitem.author.dept | MediaTek-NTU Research Center | - |
crisitem.author.orcid | 0000-0001-8936-8255 | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
crisitem.author.parentorg | Others: International Research Centers | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
顯示於: | 資訊工程學系 |
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