Sensor Fusion and Device Collaboration based Smart Plug Hub Architecture for Precise Identification of ADL in Real-Time

초록

In this paper, we propose a Smart Plug Hub Architecture for real-time measurement of Activities of Daily Living (ADL), a medical index indicating daily living performance. Currently, ADL is evaluated through patient interviews, behavioral videos, or behavioral tracking through wearable devices. However, the above methods have problems such as low accuracy and privacy violation. SPH overcomes the above problems through sensor fusion and device collaboration. SPH predicts the situation by detecting environmental changes according to human behavior through various environmental sensors. In order to analyze continuous environmental data effectively, a technique of analyzing data divided by each part is used by receiving a segmentation triggering a signal that allows data to be analyzed by region from surrounding IoT devices. By visualizing the collected data, SPH was able to predict in real-time specific human behavior in various environments.

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