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dc.contributor.authorWu, Zone-Zeen_US
dc.contributor.authorWu, Cheng-Weien_US
dc.contributor.authorVan, Lan-Daen_US
dc.contributor.authorTseng, Yu-Cheeen_US
dc.date.accessioned2018-08-21T05:57:12Z-
dc.date.available2018-08-21T05:57:12Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn2334-0983en_US
dc.identifier.urihttp://hdl.handle.net/11536/147176-
dc.description.abstractQueuing recognition is a recently new raised research topic, which uses sensors of smartphones to automatically recognize human queuing behaviors. However, existing collaborative approaches need to exchange sensor data among nearby smartphones, causing extra communication overheads and even delay. In view of this, this work proposes a new framework called Qnalyzer for queuing recognition using accelerometer and Wi-Fi signals. It consists of three tiers. The first tier is run by each individual smartphone to identify each user's context without exchanging data with nearby smartphones. A new algorithm called QCF (Queuer and non-queuer ClassiFier) is proposed, which considers mixture features of accelerometer and Wi-Fi signals to effectively identify whether the user is queuing or not. The second tier is an algorithm called QCT (Queuers ClusTering) running at the server side to effectively identify which queuers belong to which queues based on users' movement features. The third tier is an estimation model called QPE (Queue Property Estimation) for measuring waiting time, service time, and queue lengths. The Qnalyzer prototype on Android smartphones and the corresponding performance evaluations under real-life queuing scenarios are implemented. The extensive experiment results show that Qnalyzer achieves good performance with high accuracy.en_US
dc.language.isoen_USen_US
dc.subjectbehavior sensingen_US
dc.subjectgroup activity recognitionen_US
dc.subjectmachine learningen_US
dc.subjectqueuingen_US
dc.subjectmobile computingen_US
dc.titleQnalyzer: Queuing Recognition Using Accelerometer and Wi-Fi Signalsen_US
dc.typeProceedings Paperen_US
dc.identifier.journalGLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCEen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000428054300009en_US
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