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Mobile Big Data for Urban Analytics

Feature Topic

CALL FOR PAPERS

The rapid progress of urbanization, especially in developing countries, has led to many big cities, which have modernized people’s lives but also engendered big challenges such as air pollution, traffic congestion and increased energy consumption. To deal with these challenges, more effective and efficient information systems need to be developed, including communication, networking and computation infrastructures. Nowadays, sensing technologies and telecommunication infrastructures paired with powerful large-scale computing infrastructure enable the collection and processing of large quantities of diverse mobile data about urban spaces and its population, e.g., human mobility, air quality, traffic patterns, and geographical data. These mobile big data sources provide information and knowledge about a city and can help improve quality of life and functioning of cities when used appropriately. Mobile Big Data for Urban Analytics is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces such as sensors, devices, vehicles, buildings, and human inhabitants to address the urban issues faced by city information infrastructures. One important aspect for this FT (Feature Topic) is the understanding of human behavior in urban environments and the corresponding requirements in terms of human communications and their interplay and mutual influence with mobile networks and services. This FT is calling for papers that deal with the technical problems mentioned above. Topics for the FT include, but are not limited to:

  • City-wide data collection: practice and theory;
  • City-wide mobile traffic modeling, visualization, analysis, and prediction;
  • City-wide human mobility modeling, visualization, and understanding;
  • Human behavior modeling and mining in urban environment;
  • Social behavior modeling, understanding, and patterns mining in urban spaces;
  • Application of urban computing to the design of distributed and mobile urban systems;
  • Data mining of large scale urban networks and big data;
  • Urban computing applied to forwarding/routing problems of mobile networks;
  • Application of social network analysis to urban communication and computing system design;
  • Urban computing for urban networks and computation system;
  • City-wide intelligent transportation systems including vehicular networks;
  • City-wide mobile social applications in urban areas;
  • Location-based social networks enabling urban computing scenarios.

GUEST EDITORS

Pan Hui
Hong Kong University of Science and Technology, Hong Kong
panhui@cse.ust.hk

Yong Li
Tsinghua University, China
liyong07@tsinghua.edu.cn

Bo Han
AT&T Labs Research, USA
bohan@research.att.com

Jörg Ott
Technische Universität München, Germany
ott@in.tum.de

Steve Uhlig
Queen Mary University of London, UK
steve.uhlig@qmul.ac.uk

Kun Tan
Huawei Technologies, Co., Ltd., China
kun.tan@huawei.com