• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.57-64
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• 2024

In this paper, we propose a Line-of-Sight (LoS)/Non-Line-of-Sight (NLoS) identification- based Human Activity Recognition (HAR) system using Channel State Information (CSI) to improve the accuracy of HAR, which dynamically changes depending on the reception environment. to consider the reception environment of HAR system, the proposed system includes three operational phases: Preprocessing phase, Classification phase, and Activity recognition phase. In the preprocessing phase, amplitude is extracted from CSI raw data, and noise in the extracted amplitude is removed. In the Classification phase, the reception environment is categorized into LoS and NLoS. Then, based on the categorized reception environment, the HAR model is determined based on the result of the reception environment categorization. Finally, in the activity recognition phase, human actions are classified into sitting, walking, standing, and absent using the determined HAR model. To demonstrate the superiority of the proposed system, an experimental implementation was performed and the accuracy of the proposed system was compared with that of the existing HAR system. The results showed that the proposed system achieved 16.25% higher accuracy than the existing system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.105-113
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• 2008

In Ubiquitous Society, accurate Location Calculation of user's device is required to achieve the need of users. As the location calculation is processed by ranging between transceivers, if some obstacles exist between transceivers, NLoS(Non-line-of-Sight) components of received signal increase along with the reduction of LoS(Line-of-Sight) components. Therefore the location calculation error will increase due to the NLoS effect. The conventional location calculation algorithm has the original ranging error because there is no transformation of ranging information which degrades the ranging accuracy. The Iterative Calculation method which minimizes the location calculation error relys on accurately identifying NLoS or LoS condition of the tested channel. We employ Kurtosis, Mean Excess Delay and RMS Delay spread of the received signal to identify whether the tested channel is LoS or NLoS firstly. Thereafter, to minimize location calculation error, the proposed Iterative Calculation method iteratively select random range and finds the averaged target location which has high probability. The simulation results confirm the enhancement of the proposed method.