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- W3107499717 abstract "In this paper, we propose a cloud-based real-time human activity recognition system. First, we develop a wearable system that contains an Accelerometer sensor, an analog to digital converter and a WiFi module in order to sense human movement data and transmit the sensed data to cloud. Then we apply Machine Learning algorithm to classify different human activities. The proposed system is able to achieve an average of 93% accuracy in classifying the different activities efficiently." @default.
- W3107499717 created "2020-12-07" @default.
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- W3107499717 date "2020-09-28" @default.
- W3107499717 modified "2023-10-02" @default.
- W3107499717 title "Cloud-based Real-time and Remote Human Activity Recognition System using Wearable Sensors" @default.
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- W3107499717 doi "https://doi.org/10.1109/icce-taiwan49838.2020.9258050" @default.
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