Open AccessA LoRa-based Remote Gesture Monitoring System Using Deep Learning
Author(s) -
Junwei Xie,
Wei Song,
Amanda Gozho,
Fan Yu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1744/2/022133
Subject(s) - gesture , computer science , gesture recognition , wearable computer , task (project management) , transmission (telecommunications) , real time computing , deep learning , identification (biology) , wearable technology , power consumption , artificial intelligence , embedded system , power (physics) , computer hardware , engineering , telecommunications , botany , physics , systems engineering , quantum mechanics , biology
To solve the problems of high power consumption, low transmission distance and low recognition accuracy of the gesture monitoring system of traditional wearable devices, this paper designs a remote gesture monitoring system based on LoRa. In terms of data transmission, LoRa Internet of Things technology is used, which has the characteristics of low power consumption, high speed and long-distance transmission, and can meet the needs of multi-user long-term use. The identification module is built on the remote server and can be used directly without configuration. Based on the multi-sensor data, this paper also designs a deep learning model to complete the task of human gesture recognition, which can recognize 7 kinds of gesture data and the effect meets the expectations.