Abstract
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 ...
Highlights
Wireless sensor network (WSN) data are the result of measuring the available values from the physical environment
Using the Real-Time Logic (RTL)-like expression, the following temporal logic can be expressed: On the other hand, the deep learning query processing is always performed at a deterministic time because the feature set of the same size is always used, while the execution time of the query refinement may be variable depending on the situation of the arrival data
We propose a framework for analyzing and monitoring WSN data
Summary
Wireless sensor network (WSN) data are the result of measuring the available values from the physical environment. The horizontal axis of the figure represents the time, and three types of sensor values A, B, and C are being collected by the base station over time Using these data, the deep learning task performs analysis periodically. We assume a real-time system, so deep learning task has constraint that must be completed between release time and deadline This task combines the collected sensor data to generate a query and inputs the query into a deep learning analyzer for query processing. Using the RTL-like expression, the following temporal logic can be expressed: On the other hand, the deep learning query processing is always performed at a deterministic time because the feature set of the same size is always used, while the execution time of the query refinement may be variable depending on the situation of the arrival data. We can confirm that it is possible to perform the deep learning process of the streaming data with a definite time
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