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GroupSense: recognizing and understanding group physical activities using multi-device embedded sensing
journal contribution
posted on 2019-01-01, 00:00 authored by Amin B Abkenar, Seng LokeSeng Loke, Arkady ZaslavskyArkady Zaslavsky, Wenny RahayuHuman activity recognition using embedded mobile and embedded sensors is becoming increasingly important. Scaling up from individuals to groups, that is, Group Activity Recognition (GAR), has attracted significant attention recently. This article proposes a model and modeling language for GAR called GroupSense-L and a novel distributed middleware called GroupSense for mobile GAR. We implemented and tested GroupSense using smartphone sensors, smartwatch sensors, and embedded sensors in things, where we have a protocol for these different devices to exchange information required for GAR. A range of continuous group activities (from simple to fairly complex) illustrates our approach and demonstrates the feasibility of our model and richness of the proposed specialization. We then conclude with lessons learned for GAR and future work.
History
Journal
ACM transactions on embedded computing systemsVolume
17Issue
6Article number
98Pagination
1 - 26Publisher
Association for Computing MachineryLocation
New York, N.Y.Publisher DOI
ISSN
1539-9087Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2019, Association for Computing MachineryUsage metrics
Categories
Keywords
Computer systems organizationEmbedded systemsHardwareSensor devices and platformsGeneral and referenceDesignHuman-centered computingUbiquitous and mobile computingGroup activity recognition (GAR)context-aware computingsensor reasoningScience & TechnologyTechnologyComputer Science, Hardware & ArchitectureComputer Science, Software EngineeringComputer ScienceACTIVITY RECOGNITIONINTERNETComputer SoftwareDistributed Computing
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