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Low-Cost and Device-Free Human Activity Recognition Based on Hierarchical Learning Model
2021
Sensors
Human activity recognition (HAR) has been a vital human–computer interaction service in smart homes. It is still a challenging task due to the diversity and similarity of human actions. In this paper, a novel hierarchical deep learning-based methodology equipped with low-cost sensors is proposed for high-accuracy device-free human activity recognition. ESP8266, as the sensing hardware, was utilized to deploy the WiFi sensor network and collect multi-dimensional received signal strength
doi:10.3390/s21072359
pmid:33800704
fatcat:ohis4uevujc7fptxqnitwhtzey