mk-sense: An Extensible Platform to Conduct Multi-institutional Mobile Sensing Campaigns
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  • 关键词:Mobile devices ; Smartphones ; Sensing campaign ; Data management application
  • 刊名:Lecture Notes in Computer Science
  • 出版年:2016
  • 出版时间:2016
  • 年:2016
  • 卷:10069
  • 期:1
  • 页码:207-216
  • 全文大小:950 KB
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  • 作者单位:Netzahualcóyotl Hernández (17)
    Bert Arnrich (18)
    Jesús Favela (17)
    Remzi Gökhan (18)
    Cem Ersoy (18)
    Burcu Demiray (19)
    Jesús Fontecha (20)

    17. Computer Science Department, CICESE Research Center, Ensenada, Mexico
    18. Computer Engineering Department, Boğaziçi University, Istanbul, Turkey
    19. Psychology Department, University of Zürich, Zurich, Switzerland
    20. Computer Science Department, University of Castilla-La Mancha, Ciudad Real, Spain
  • 丛书名:Ubiquitous Computing and Ambient Intelligence
  • ISBN:978-3-319-48746-5
  • 刊物类别:Computer Science
  • 刊物主题:Artificial Intelligence and Robotics
    Computer Communication Networks
    Software Engineering
    Data Encryption
    Database Management
    Computation by Abstract Devices
    Algorithm Analysis and Problem Complexity
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1611-3349
  • 卷排序:10069
文摘
Mobile sensing has become a growing area of research in pervasive healthcare. In this paper we present mk-sense, an open framework for mobile sensing on smartphones. mk-sense is an initiative to reduce the efforts of researchers involved in multi-institutional sensing campaign. It is designed to facilitate the collaboration of researchers that run simultaneous data collection efforts in different locations. We illustrate the use of mk-sense with two cross-cultural studies conducted in four different countries (Turkey, Mexico, Switzerland, and Spain) with a total of 77 participants. In this paper, we describe the challenges and experience of conducting research in the wild by using mk-sense as sensing platform. Finally, we present how the conducted studies influenced the design decisions of mk-sense, including features, and tools to monitor data gathering in real-time.

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