MViewer: Mobile phone spatiotemporal data viewer

Jiansu Pu, Siyuan Liu, Panpan Xu, Huamin Qu, Lionel M. Ni

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Nowadays movement patterns and people's behavioral models are needed for traffic engineers and city planners. These observations could be used to reason about mobility and its sustainability and to support decision makers with reliable information. The very same knowledge about human diaspora and behavior extracted from these data is also valuable to the urban planner, so as to localize new services, organize logistics systems and to detect changes as they occur in the movement behavior. Moreover, it is interesting to investigate movement in places like a shopping area or a working district either for commercial purposes or for improving the service quality. These kinds of tracking data are made available by wireless and mobile communication technologies. It is now possible to record and collect a large amount of mobile phone calls in a city. Technologies for object tracking have recently become affordable and reliable and hence we were able to collect mobile phone data from a city in China from January 1, 2008 to December 31, 2008. The large amount of phone call records from mobile operators can be considered as life mates and sensors of persons to inform howmany people are present in any given area and how many are entering or leaving. Each phone call record usually contains the caller and callee IDs, date and time, and the base station where the phone calls are made. As mobile phones are widely used in our daily life, many human behaviors can be revealed by analyzing mobile phone data. Through mobile phones, we can learn the information about locations, communications between mobile phone users during their daily lives. In this work, we propose a comprehensive visual analysis system named as MViewer, Mobile phone spatiotemporal data Viewer, which is the first system to visualize and analyze the population'smobility patterns from millions of phone call records. Our system consists of three major components: 1) visual analysis of user groups in a base station; 2) visual analysis of the mobility patterns on different user groups making phone calls in certain base stations; 3) visual analysis of handoff phone call records. Some well-established visualization techniques such as parallel coordinates and pixelbased representations have been integrated into our system. We also develop a novel visualization schemes, Voronoidiagram-based visual encoding to reveal the unique features of mobile phone data. We have applied our system to real mobile phone datasets that are kindly provided by our project partners and obtained some interesting findings regarding people's mobility patterns.

Original languageEnglish (US)
Pages (from-to)298-315
Number of pages18
JournalFrontiers of Computer Science
Volume8
Issue number2
DOIs
StatePublished - Jan 1 2014

Fingerprint

Spatio-temporal Data
Mobile Phone
Mobile phones
Base stations
Visualization
Handoff
Service Quality
Mobile Communication
Voronoi Diagram
Communication
Object Tracking
Human Behavior
Sustainability
Decision Support
Systems Analysis
Date
Wireless Communication
Logistics
Sustainable development
China

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Pu, Jiansu ; Liu, Siyuan ; Xu, Panpan ; Qu, Huamin ; Ni, Lionel M. / MViewer : Mobile phone spatiotemporal data viewer. In: Frontiers of Computer Science. 2014 ; Vol. 8, No. 2. pp. 298-315.
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MViewer : Mobile phone spatiotemporal data viewer. / Pu, Jiansu; Liu, Siyuan; Xu, Panpan; Qu, Huamin; Ni, Lionel M.

In: Frontiers of Computer Science, Vol. 8, No. 2, 01.01.2014, p. 298-315.

Research output: Contribution to journalArticle

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