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dc.contributor.author김정선-
dc.date.accessioned2018-04-23T05:57:42Z-
dc.date.available2018-04-23T05:57:42Z-
dc.date.issued2016-08-
dc.identifier.citationMOBILE INFORMATION SYSTEMS, V. 2016, Article ID 2316757en_US
dc.identifier.issn1574-017X-
dc.identifier.urihttps://www.hindawi.com/journals/misy/2016/2316757/abs/-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/70337-
dc.description.abstractNowadays, human activity recognition (HAR) plays an important role inwellness-care and context-aware systems. Human activities can be recognized in real-time by using sensory data collected from various sensors built in smart mobile devices. Recent studies have focused on HAR that is solely based on triaxial accelerometers, which is the most energy-efficient approach. However, such HAR approaches are still energy-inefficient because the accelerometer is required to run without stopping so that the physical activity of a user can be recognized in real-time. In this paper, we propose a novel approach for HAR process that controls the activity recognition duration for energy-efficient HAR. We investigated the impact of varying the acceleration-sampling frequency and window size for HAR by using the variable activity recognition duration (VARD) strategy. We implemented our approach by using an Android platform and evaluated its performance in terms of energy efficiency and accuracy. The experimental results showed that our approach reduced energy consumption by a minimum of about 44.23% andmaximum of about 78.85% compared to conventional HAR without sacrificing accuracy.en_US
dc.language.isoen_USen_US
dc.publisherHINDAWI PUBLISHING CORPen_US
dc.subjectCAREen_US
dc.subjectFALL DETECTION SYSTEMen_US
dc.subjectPHYSICAL-ACTIVITYen_US
dc.subjectTRIAXIAL ACCELEROMETERen_US
dc.subjectCONTEXTen_US
dc.titleEnergy-Efficient Real-Time Human Activity Recognition on Smart Mobile Devicesen_US
dc.typeArticleen_US
dc.identifier.doi10.1155/2016/2316757-
dc.relation.page1-12-
dc.relation.journalMOBILE INFORMATION SYSTEMS-
dc.contributor.googleauthorLee, Jin-
dc.contributor.googleauthorKim, Jungsun-
dc.relation.code2016006453-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF COMPUTING[E]-
dc.sector.departmentDIVISION OF COMPUTER SCIENCE-
dc.identifier.pidkimjs-
Appears in Collections:
COLLEGE OF COMPUTING[E](소프트웨어융합대학) > COMPUTER SCIENCE(소프트웨어학부) > Articles
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