{"title":"WiFiTuned: Monitoring Engagement in Online Participation by Harmonizing WiFi and Audio","authors":"Vijay Kumar Singh, Pragma Kar, Ayush Madhan Sohini, Madhav Rangaiah, Sandip Chakraborty, Mukulika Maity","doi":"10.1145/3577190.3614108","DOIUrl":null,"url":null,"abstract":"This paper proposes a multi-modal, non-intrusive and privacy preserving system WiFiTuned for monitoring engagement in online participation i.e., meeting/classes/seminars. It uses two sensing modalities i.e., WiFi CSI and audio for the same. WiFiTuned detects the head movements of participants during online participation through WiFi CSI and detects the speaker’s intent through audio. Then it correlates the two to detect engagement. We evaluate WiFiTuned with 22 participants and observe that it can detect the engagement level with an average accuracy of more than .","PeriodicalId":93171,"journal":{"name":"Companion Publication of the 2020 International Conference on Multimodal Interaction","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Companion Publication of the 2020 International Conference on Multimodal Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3577190.3614108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a multi-modal, non-intrusive and privacy preserving system WiFiTuned for monitoring engagement in online participation i.e., meeting/classes/seminars. It uses two sensing modalities i.e., WiFi CSI and audio for the same. WiFiTuned detects the head movements of participants during online participation through WiFi CSI and detects the speaker’s intent through audio. Then it correlates the two to detect engagement. We evaluate WiFiTuned with 22 participants and observe that it can detect the engagement level with an average accuracy of more than .