期刊
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
卷 35, 期 5, 页码 1118-1131出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2017.2679658
关键词
Device-free sensing; human activities; WiFi; CSI
资金
- National Natural Science Foundation of China [61373129, 61472184, 61321491, 61472185]
- National Science Foundation [CNS-1318563, CNS-1524698, CNS-1421407, CNS-1565609, IIP-1632051]
- Collaborative Innovation Center of Novel Software Technology and Industrialization
- Jiangsu High-Level Innovation and Entrepreneurship (Shuangchuang) Program
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [1565609, 1421407] Funding Source: National Science Foundation
Since human bodies are good reflectors of wireless signals, human activities can be recognized by monitoring changes in WiFi signals. However, existing WiFi-based human activity recognition systems do not build models that can quantify the correlation between WiFi signal dynamics and human activities. In this paper, we propose a Channel State Information (CSI)-based human Activity Recognition and Monitoring system (CARM). CARM is based on two theoretical models. First, we propose a CSI-speed model that quantifies the relation between CSI dynamics and human movement speeds. Second, we propose a CSI-activity model that quantifies the relation between human movement speeds and human activities. Based on these two models, we implemented the CARM on commercial WiFi devices. Our experimental results show that the CARM achieves recognition accuracy of 96% and is robust to environmental changes.
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