Transportation Type Identification by using Machine Learning Algorithms with Cellular Information

Yi Hao Lin, Jyh-Cheng Chen, Chih Yu Lin, Bo Yue Su, Pei Yu Lee

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

It is crucial for future 5G networks to intelligently understand how users move so that the networks can allocate different resources efficiently. In this paper, we try to find practical features to identify four common types of motorized transportations, including High-Speed Rail (HSR), subway, railway, and highway. We propose a system architecture that can provide accurate, real-time, and adaptive solution by using cellular information only. Because we do not use GPS as that in most of the prior studies, we can reduce energy consumption, size of log data, and computational time. Around 500-hour data are collected for performance evaluation. Experimental results confirm the effectiveness of the proposed algorithm, which can improve well-known machine learning algorithms to approximately 98% classification accuracy. The results also show that battery consumption can be reduced about 37%.

原文English
主出版物標題2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁數7
ISBN(電子)9781538680889
DOIs
出版狀態Published - 20 5月 2019
事件2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China
持續時間: 20 5月 201924 5月 2019

出版系列

名字IEEE International Conference on Communications
2019-May
ISSN(列印)1550-3607

Conference

Conference2019 IEEE International Conference on Communications, ICC 2019
國家/地區China
城市Shanghai
期間20/05/1924/05/19

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