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The Impacts of CSI Temporal Variations on CSI-based Occupancy Monitoring Systems: An Exploratory Study
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Hoonyong | - |
dc.contributor.author | Ahn, Changbum Ryan | - |
dc.contributor.author | Choi, Nakjung | - |
dc.date.accessioned | 2024-05-20T06:12:51Z | - |
dc.date.available | 2024-05-20T06:12:51Z | - |
dc.date.created | 2024-05-20 | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | BuildSys 2020 - Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp.278-281 | - |
dc.identifier.uri | https://hdl.handle.net/10371/203456 | - |
dc.description.abstract | Channel State Information (CSI) has been used for an alternative sensing source for occupancy monitoring systems to classify activities of daily living (ADLs). Previous studies have proposed learning-based activity classification models, which require similar distributions of CSI for training and testing datasets. However, as CSI varies even in a static environment, the activity classification model trained with data collected in a particular day would be invalid for other time frames. In this context, this study examines the impacts of the CSI temporal variations on the learning-based occupant activity monitoring systems. An experiment was performed to collect the CSI data while an occupant performed daily activities for six days. Three learning-based activity classification models reconstructed from the previous studies were trained and tested with time-dependent cross validation. The performances of the benchmark models were greatly degraded (below 60%) with testing data collected at different days than the training data, while their performances with testing data collected at the same day with training data were over 90%. This study also explores the opportunity to address this issue with transfer learning techniques. | - |
dc.language | 영어 | - |
dc.publisher | Association for Computing Machinery, Inc | - |
dc.title | The Impacts of CSI Temporal Variations on CSI-based Occupancy Monitoring Systems: An Exploratory Study | - |
dc.type | Article | - |
dc.identifier.doi | 10.1145/3408308.3427624 | - |
dc.citation.journaltitle | BuildSys 2020 - Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation | - |
dc.identifier.scopusid | 2-s2.0-85097182644 | - |
dc.citation.endpage | 281 | - |
dc.citation.startpage | 278 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Ahn, Changbum Ryan | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordAuthor | Channel State Information | - |
dc.subject.keywordAuthor | Indoor Activity Classification | - |
dc.subject.keywordAuthor | Learning-based Classification | - |
dc.subject.keywordAuthor | Temporal Variation | - |
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- College of Engineering
- Department of Architecture & Architectural Engineering
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