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A traffic pattern detection algorithm based on multimodal sensing
Qin, Yanjun1; Luo, Haiyong2; Zhao, Fang1; Zhao, Zhongliang3; Jiang, Mengling1
2018-10-25
发表期刊INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
ISSN1550-1477
卷号14期号:10页码:16
摘要Nowadays, smartphones are widely and frequently used in people's daily lives for their powerful functions, which generate an enormous amount of data accordingly. The large volume and various types of data make it possible to accurately identify people's travel behaviors, that is, transportation mode detection. Using the transportation mode detection, results can increase commuting efficiency and optimize metropolitan transportation planning. Although much work has been done on transportation mode detection problem, the accuracy is not sufficient. In this article, an accurate traffic pattern detection algorithm based on multimodal sensing is proposed. This algorithm first extracts various sensory features and semantic features from four types of sensor (i.e. accelerator, gyroscope, magnetometer, and barometer). These sensors are commonly embedded in commodity smartphones. All the extracted features are then fed into a convolutional neural network to infer traffic patterns. Extensive experimental results show that the proposed scheme can identify four transportation patterns with 94.18% accuracy.
关键词Deep learning low power consumption transportation mode detection multimodal sensing performance comparison
DOI10.1177/1550147718807832
收录类别SCI
语种英语
资助项目National Key Research and Development Program[2018YFB0505200] ; National Natural Science Foundation of China[61872046] ; Open Project of the Beijing Key Laboratory of Mobile Computing and Pervasive Device
WOS研究方向Computer Science ; Telecommunications
WOS类目Computer Science, Information Systems ; Telecommunications
WOS记录号WOS:000449110400001
出版者SAGE PUBLICATIONS INC
引用统计
被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/3654
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Luo, Haiyong
作者单位1.Beijing Univ Posts & Telecommun, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, 6 Kexueyuan South Rd, Beijing 100190, Peoples R China
3.Univ Bern, Inst Comp Sci, Bern, Switzerland
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GB/T 7714
Qin, Yanjun,Luo, Haiyong,Zhao, Fang,et al. A traffic pattern detection algorithm based on multimodal sensing[J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS,2018,14(10):16.
APA Qin, Yanjun,Luo, Haiyong,Zhao, Fang,Zhao, Zhongliang,&Jiang, Mengling.(2018).A traffic pattern detection algorithm based on multimodal sensing.INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS,14(10),16.
MLA Qin, Yanjun,et al."A traffic pattern detection algorithm based on multimodal sensing".INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 14.10(2018):16.
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