Journal
IEEE COMMUNICATIONS MAGAZINE
Volume 55, Issue 10, Pages 91-97Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MCOM.2017.1700143
Keywords
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Funding
- National Key Research and Development Plan [2016YFB1001200]
- Peking University Information Technology Institute (Tianjin Binhai)
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Recently, device-free WiFi CSI-based human behavior recognition has attracted a great amount of interest as it promises to provide a ubiquitous sensing solution by using the pervasive WiFi infrastructure. While most existing solutions are pattern-based, applying machine learning techniques, there is a recent trend of developing accurate models to reveal the underlining radio propagation properties and exploit models for fine-grained human behavior recognition. In this article, we first classify the existing work into two categories: pattern-based and model-based recognition solutions. Then we review and examine the two approaches together with their enabled applications. Finally, we show the favorable properties of model-based approaches by comparing them using human respiration detection as a case study, and argue that our proposed Fresnel zone model could be a generic one with great potential for device-free human sensing using fine-grained WiFi CSI.
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