Device-Free Indoor Human Activity Recognition Using Wi-Fi RSSI: Machine Learning Approaches

Chao Feng Hsieh, Yi Chu Chen, Cheng Ying Hsieh, Meng Lin Ku

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

A device-free methodology is proposed to recognize the human activity in indoor environments using WiFi received signal strength indication (RSSI), and several machine learning (ML) approaches are investigated to realize the activity detection. With multiple access points (APs), the RSSIs are synchronously collected at multiple mobile phones (MPs) with different locations over a time duration and served as input data for training the detectors, enabling us to recognize the human activities of either moving or stationary. Extensive real experiments are conducted in the frequency bands of 2.4 GHz and 5 GHz, and the results show that the proposed methods can achieve over 95% recognition accuracy in the 5 GHz frequency band.

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主出版物標題2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728173993
DOIs
出版狀態已出版 - 28 9月 2020
事件7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan
持續時間: 28 9月 202030 9月 2020

出版系列

名字2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

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???event.eventtypes.event.conference???7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
國家/地區Taiwan
城市Taoyuan
期間28/09/2030/09/20

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