Abstract
Knowing human activity in each day is relevant information in several purposes. However, existing activity recognition systems have limitation to identify the human activity because they cannot get the appropriate information for recognition. To address this limitation, we present three relevant components in Context-aware Activity Recognition Engine (CARE) architecture for organizing context-aware information in home. First, we introduce Context Sensor Network (CSN). The CSN provides the raw environment information from the diversity of sensors. Second, data manager component is proposed to process the pre-processing in the raw data from the CSN. The data must be normalized and transformed in order to make the system more efficient. The last component is system repository that composes of three essential tasks for controlling the information in the system. In this paper, the ontology based activity recognition (OBAR) system is used to evaluate the data from proposed components. The high accuracy of results can refer to the well organization of proposed components.
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Wongpatikaseree, K., Kim, J., Makino, Y., Lim, A.O., Tan, Y. (2013). Architecture for Organizing Context-Aware Data in Smart Home for Activity Recognition System. In: Streitz, N., Stephanidis, C. (eds) Distributed, Ambient, and Pervasive Interactions. DAPI 2013. Lecture Notes in Computer Science, vol 8028. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39351-8_20
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DOI: https://doi.org/10.1007/978-3-642-39351-8_20
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