Using Latent Knowledge to Improve Real-Time Activity Recognition for Smart IoT.

IEEE Transactions on Knowledge and Data Engineering(2020)

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摘要
Real-time/online activity recognition (AR) is an important technology in smart Internet of Things (IoT) systems where users are assisted by smart devices in their daily activities. How to generate appropriate feature representation from sensor event streaming is a challenging issue for accurate and efficient real-time AR. Previous AR models that rely on explicit domain knowledge are not appropriat...
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关键词
Hidden Markov models,Probability distribution,Real-time systems,Windows,Deep learning,Microsoft Windows
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