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• W2768702910 abstract "With the continuing penetration of sensor devices and the development of wireless communication techniques, increasing number of applications involving context awareness in ubiquitous computing have been used in daily life. How to collect data from mobile devices at a low energy cost and to mine contextual habits of users remains a key challenge for ubiquitous computing. We proposed an efficient context- awareness computing middleware system, Senz. By leveraging high-efficiency mobile data transmission method, using high-performance context recognition algorithms, and combining mobile data with online third-party data, this middleware system can recognize various user behavior patterns reliably, accurately and efficiently. Experiments show that the Senz recognition accuracy of context activity is above 83% on average and the energy cost is relatively low. By integrating Senz SDK and cloud computing engine, developers can build rich user experience apps with better understanding of users' behavior data and providing various personalized contextual services." @default.
• W2768702910 created "2017-12-04" @default.
• W2768702910 creator A5016858164 @default.
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• W2768702910 date "2017-06-01" @default.
• W2768702910 modified "2023-09-24" @default.
• W2768702910 title "Senz: A Context Awareness Middleware System Used in Mobile Devices" @default.
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• W2768702910 doi "https://doi.org/10.1109/vtcspring.2017.8108299" @default.
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