Temporal stability on human activity recognition based on Wi-Fi CSI
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Altres documents de l'autoria: Matey-Sanz, Miguel; Torres-Sospedra, Joaquín; Moreira, Adriano
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comunitat-uji-handle2:10234/7038
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10.1109/IPIN57070.2023.10332214 |
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Títol
Temporal stability on human activity recognition based on Wi-Fi CSIData de publicació
2023-12-06Editor
IEEEISBN
9798350320114ISSN
2471‐917XCita bibliogràfica
M. Matey-Sanz, J. Torres-Sospedra and A. Moreira (2023) "Temporal Stability on Human Activity Recognition based on Wi-Fi CSI," 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nuremberg, Germany, 2023, pp. 1-6,Tipus de document
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Resum
Over the last years, numerous studies have emerged using Wi-Fi channel state information, enabling device-free (passive) sensing for applications such as motion detection, indoor positioning or human activity recogn ... [+]
Over the last years, numerous studies have emerged using Wi-Fi channel state information, enabling device-free (passive) sensing for applications such as motion detection, indoor positioning or human activity recognition. More recently, the development framework for the low-cost ESP32 microcontrollers has added support for obtaining channel state information data. In this work, we collected channel state information data for human activity recognition, where activities are relatively localized with respect to the Wi-Fi infrastructure. The data was collected in several runs, duly spaced in time, and a convolutional neural network model was used for the classification of activities. Classification performance evaluation showed a clear degradation when a model evaluated with data collected 10 minutes after the data used for training showed a 52% relative loss in the accuracy of the classification. [-]
Descripció
Ponència presentada en: 2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN)
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13th International Conference on Indoor Positioning and Indoor Navigation (IPIN) (2023)Drets d'accés
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