Abstract
Research and product development using machine-learning technology is ongoing worldwide. It is especially active in the field of predicting a person's activity. In this paper, a person's presence and movement are determined through machine learning by using radar signals. The preprocessing stage of receiving and processing radar signals produces a basic dataset. Next, we create a machine-learning model and conduct a prediction experiment with four test-sets that is created for this paper. Experiments conducted in this study showed a high level of classification accuracy. However, data sets, pre-treated only by classification of signals, seemed to be quite sensitive to the quality of the data when used as a feature of machine learning.
| Original language | English |
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| Title of host publication | ICTC 2019 - 10th International Conference on ICT Convergence |
| Subtitle of host publication | ICT Convergence Leading the Autonomous Future |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 12-17 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728108926 |
| DOIs | |
| State | Published - Oct 2019 |
| Event | 10th International Conference on Information and Communication Technology Convergence, ICTC 2019 - Jeju Island, Korea, Republic of Duration: 16 Oct 2019 → 18 Oct 2019 |
Publication series
| Name | ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future |
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Conference
| Conference | 10th International Conference on Information and Communication Technology Convergence, ICTC 2019 |
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| Country/Territory | Korea, Republic of |
| City | Jeju Island |
| Period | 16/10/19 → 18/10/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Machine Learning
- SVM
- UWB Impulse Radar