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This article addresses this gap by proposing a low-cost and non-intrusive method for monitoring social distancing within a given space, using Channel State Information (CSI) from passive WiFi sensing. By exploiting the frequency selective behavior of CSI with a Support Vector Machine (SVM) classifier, we achieve an improvement in accuracy over existing crowd counting works. Our system counts the number of occupants with a 93% accuracy rate in an elevator setting and predicts whether the COVID-Safe limit is breached with a 97% accuracy rate. We also demonstrate the occupant counting capability of the system in a commercial office setting, achieving 97% accuracy. Our proposed occupancy monitoring outperforms existing methods by at least 7%. Overall, the proposed framework is inexpensive, requiring only one device that passively collects data and a lightweight supervised learning algorithm for prediction. Our lightweight model and accuracy improvements are necessary contributions for WiFi-based counting to be suitable for COVID-specific applications.<\/jats:p>","DOI":"10.1145\/3472668","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T19:02:52Z","timestamp":1631127772000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":32,"title":["COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples"],"prefix":"10.1145","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2063-6431","authenticated-orcid":false,"given":"Junye","family":"Li","sequence":"first","affiliation":[{"name":"School of Electrical Engineering and Telecommunications, University of New South Wales, High St, Sydney, NSW"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aryan","family":"Sharma","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Telecommunications, University of New South Wales, High St, Sydney, NSW"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deepak","family":"Mishra","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Telecommunications, University of New South Wales, High St, Sydney, NSW"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gustavo","family":"Batista","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of New South Wales, High St, Sydney, NSW"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aruna","family":"Seneviratne","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Telecommunications, University of New South Wales, High St, Sydney, NSW"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,9,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Airista. 2020. 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