抄録
In this paper, we performed human moving pattern recognition using communication quality: cellular download throughputs, Received Signal Strength Indicators (RSSIs) and cellular base station IDs. We apply three machine learning algorithms, such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Random Forest (RF) and evaluate recognition accuracy of human moving patterns. Results conclude that the communication quality can recognize moving patterns with high accuracy.
本文言語 | English |
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ホスト出版物のタイトル | 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017 |
出版社 | Institute of Electrical and Electronics Engineers Inc. |
ページ | 1-2 |
ページ数 | 2 |
巻 | 2017-January |
ISBN(電子版) | 9781509040452 |
DOI | |
出版ステータス | Published - 2017 12 19 |
イベント | 6th IEEE Global Conference on Consumer Electronics, GCCE 2017 - Nagoya, Japan 継続期間: 2017 10 24 → 2017 10 27 |
Other
Other | 6th IEEE Global Conference on Consumer Electronics, GCCE 2017 |
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Country | Japan |
City | Nagoya |
Period | 17/10/24 → 17/10/27 |
ASJC Scopus subject areas
- Media Technology
- Instrumentation
- Electrical and Electronic Engineering