demonstration

Demo: Data Analysis and Visualization in Bike-Sharing Systems

Authors:

Ji Hu,

Jiming ChenAuthors Info & Claims

MobiSys '16 Companion: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion

Page 128

https://doi.org/10.1145/2938559.2938580

Published: 25 June 2016 Publication History

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Abstract

Public bike-sharing systems (BSS) are booming all around the world, providing a flexible trip mode for people in cities. However, the imbalance usage among stations is causing problems for both system operators and users. As a first step to address this challenge, a recent paper has proposed a spatio-temporal bicycle mobility model based on historical bike-sharing data, and devised a traffic prediction mechanism on a per-station basis with sub-hour granularity. To better demonstrate the mobility model and prediction, we develop this data analysis and visualization system, not only presenting massive real-time prediction results but also serving as a platform for human mobility analysis.

References

[1]

Zidong Yang, Ji Hu, Yuanchao Shu, Peng Cheng, Jiming Chen, and Thomas Moscibroda. Mobility Modeling and Prediction in Bike-Sharing Systems. In ACM Mobisys, 2016.

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[2]

Jiming Chen, Weiqiang Xu, Shibo He, Youxian Sun, Preetha Thulasiraman, and Xuemin Sherman Shen. Utility-based asynchronous flow control algorithm for wireless sensor networks. Selected Areas in Communications, IEEE Journal on, 28(7):1116--1126, 2010.

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[3]

Bike-sharing demo video. http://www.sensornet.cn/bikevis/.

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Cited By

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Chang XFeng ZWu JSun HWang GBao X(2022)Understanding and Predicting the Short-Term Passenger Flow of Station-Free Shared Bikes: A Spatiotemporal Deep Learning ApproachIEEE Intelligent Transportation Systems Magazine10.1109/MITS.2021.304936214:4(73-85)Online publication date: Jul-2022
https://doi.org/10.1109/MITS.2021.3049362
Ban SHyun K(2019)Curvature-based distribution algorithmJournal of Visualization10.1007/s12650-019-00557-622:3(587-607)Online publication date: 25-May-2019
https://dl.acm.org/doi/10.1007/s12650-019-00557-6

Index Terms

Demo: Data Analysis and Visualization in Bike-Sharing Systems
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing theory, concepts and paradigms
      1. Mobile computing
  2. Visualization
    1. Visualization systems and tools

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Published In

MobiSys '16 Companion: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion

June 2016

172 pages

ISBN:9781450344166

DOI:10.1145/2938559

General Chairs:
Rajesh Balan
Singapore Management University
,
Archan Misra
Singapore Management University
,
Program Chairs:
Landon Cox
Duke University
,
Yutaka Arakawa
NAIST
,
Xia Zhou
Dartmouth College
,
Robert LiKamWa
Rice University

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGOPS: ACM Special Interest Group on Operating Systems

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Association for Computing Machinery

New York, NY, United States

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Published: 25 June 2016

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Ministry of Science and Technology of the People's Republic of China

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SIGMOBILE

MobiSys'16: The 14th Annual International Conference on Mobile Systems, Applications, and Services

June 25 - 30, 2016

Singapore, Singapore

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Chang XFeng ZWu JSun HWang GBao X(2022)Understanding and Predicting the Short-Term Passenger Flow of Station-Free Shared Bikes: A Spatiotemporal Deep Learning ApproachIEEE Intelligent Transportation Systems Magazine10.1109/MITS.2021.304936214:4(73-85)Online publication date: Jul-2022
https://doi.org/10.1109/MITS.2021.3049362
Ban SHyun K(2019)Curvature-based distribution algorithmJournal of Visualization10.1007/s12650-019-00557-622:3(587-607)Online publication date: 25-May-2019
https://dl.acm.org/doi/10.1007/s12650-019-00557-6

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Mobility Modeling and Prediction in Bike-Sharing Systems

Demo: SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory

Accurate mobility modeling and location prediction based on pattern analysis of handover series in mobile networks

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