Deep learning-based real-time query processing for wireless sensor network
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초록

The data collected from wireless sensor network indicate the system status, the environment status, or the health condition of human being, and we can use the wireless sensor network data to carry out appropriate work by processing it. In recent years, using deep learning, it is possible to construct a more intelligent context-aware system by predicting future situations as well as monitoring the current state. In this article, we propose a monitoring framework for wireless sensor network streaming data analysis based on deep learning. In particular, in an environment where time requirements are strictly enforced, data analysis results must be derived within a deterministic time. Therefore, we conduct query refinement adaptively to enable timely analysis of wireless sensor network data in the predictor. Even if some sensor data that is not synchronized in time are included or even if some data have not arrived yet, reasonably accurate query analysis results can be obtained within the deadline by performing the proposed method.

키워드

Wireless sensor networkquery processingdeep learningreal-time systemmonitoringNEURAL-NETWORKSSYSTEMS
제목
Deep learning-based real-time query processing for wireless sensor network
저자
Lee, Ki-SeongLee, Sun-RoKim, YoungminLee, Chan Gun
DOI
10.1177/1550147717707896
발행일
2017-05
유형
Article
저널명
International Journal of Distributed Sensor Networks
13
5

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