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The traditional air gesture recognition method mainly depends on external equipment (such as special sensors and cameras) whose costs are high and also with a limited application scene. In this paper, we attempt to utilize channel state information (CSI) derived from a WLAN physical layer, a Wi-Fibased air gesture recognition system, namely, WiNum, which solves the problems of users\u2019 privacy and energy consumption compared with the approaches using wearable sensors and depth cameras. In the process of recognizing the WiNum method, the collected raw data of CSI should be screened, among which can reflect the gesture motion. Meanwhile, the screened data should be preprocessed by noise reduction and linear transformation. After preprocessing, the joint of amplitude information and phase information is extracted, to match and recognize different air gestures by using the S-DTW algorithm which combines dynamic time warping algorithm (DTW) and support vector machine (SVM) properties. Comprehensive experiments demonstrate that under two different indoor scenes, WiNum can achieve higher recognition accuracy for air number gestures; the average recognition accuracy of each motion reached more than 93%, in order to achieve effective recognition of air gestures.<\/jats:p>","DOI":"10.1155\/2020\/8546237","type":"journal-article","created":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T23:34:24Z","timestamp":1597361664000},"page":"1-14","source":"Crossref","is-referenced-by-count":12,"title":["Air Gesture Recognition Using WLAN Physical Layer Information"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9655-0044","authenticated-orcid":true,"given":"Xiaochao","family":"Dang","sequence":"first","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"},{"name":"Gansu Internet of Things Engineering Research Center, Lanzhou 730070, 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