Browsing by Author "Su, Bo-Yue"

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SensingGO - Toward Mobile/Cellular Data Measurement with Social and Rewarding Activities
(2018-01-01)
Lin, Yi-Hao
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Chen, Jyh-Cheng
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Lin, Chih-Yu
;
Su, Bo-Yue
;
Lee, Pei-Yu
Mobile Crowd Sensing (MCS) is a promising paradigm to collect large-scale network data globally. However, how to motivate people to collect and share data is a challenge. We believe the major reason why many MCS systems are not pervasive is because there are no incentives for people to use them. In this paper, we present SensingGO, a system which encourages people to keep sensing data by integrating incentive mechanisms. The sensed data are then transmitted to our backend server. The data we collected and the source code of SensingGO are open to anyone freely. We also demonstrate the analysis of real mobile data collected from SensingGO.
Transportation Type Identification by using Machine Learning Algorithms with Cellular Information
(2019-01-01)
Lin, Yi-Hao
;
Chen, Jyh-Cheng
;
Lin, Chih-Yu
;
Su, Bo-Yue
;
Lee, Pei-Yu
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%.