000182084 001__ 182084
000182084 005__ 20180913061625.0
000182084 0247_ $$2doi$$a10.1109/MC.2012.393
000182084 022__ $$a0018-9162
000182084 02470 $$2ISI$$a000314943300014
000182084 037__ $$aARTICLE
000182084 245__ $$aOpportunistic human activity and context recognition
000182084 269__ $$a2013
000182084 260__ $$aLos Alamitos$$bInstitute of Electrical and Electronics Engineers$$c2013
000182084 300__ $$a10
000182084 336__ $$aJournal Articles
000182084 520__ $$aAlthough the Internet of Things allows seamless access to billions of sensors readily deployed throughout the world, current context- and activity-recognition approaches restrict ambient intelligence to domains where dedicated sensors are deployed. The big data delivered by the Internet of Things calls for a new opportunistic recognition paradigm. Instead of setting-up information sources for a specific recognition goal, the methods themselves adapt to the data available at any time. We present enabling methods that allow for opportunistic recognition in dynamic sensor configurations. This could be the missing link to fulfill the promise of ambient intelligence anywhere.
000182084 6531_ $$aWearable AI
000182084 6531_ $$aPervasive Computing
000182084 6531_ $$aWireless Sensor Networks
000182084 6531_ $$aDesign Methodology
000182084 6531_ $$a[Opportunity]
000182084 700__ $$aRoggen, Daniel
000182084 700__ $$aLukowicz, Paul
000182084 700__ $$aFerscha, Alois
000182084 700__ $$0240030$$aMillán, José del R.$$g149175
000182084 700__ $$aTröster, Gerhard
000182084 700__ $$0241256$$aChavarriaga, Ricardo$$g137762
000182084 773__ $$j46$$k2$$q36-45$$tComputer -IEEE Computer Society-
000182084 8564_ $$s3553092$$uhttps://infoscience.epfl.ch/record/182084/files/RoggenLuFeMiTrCh12.pdf$$yn/a$$zn/a
000182084 909C0 $$0252018$$pCNBI$$xU12103
000182084 909C0 $$0252517$$pCNP$$xU12599
000182084 909CO $$ooai:infoscience.tind.io:182084$$pSTI$$particle
000182084 917Z8 $$x137762
000182084 917Z8 $$x137762
000182084 917Z8 $$x137762
000182084 917Z8 $$x137762
000182084 917Z8 $$x137762
000182084 917Z8 $$x137762
000182084 917Z8 $$x137762
000182084 937__ $$aEPFL-ARTICLE-182084
000182084 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000182084 980__ $$aARTICLE