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With the phones in their pockets, millions of people have access to sensing, computation, and connectivity, making it possible to harness the power of the crowd to collect and share data about their surroundings and experiences on a massive scale. Crowdsensing/crowdsourcing is a novel data collection paradigm that leverages this vast mobile sensor network, making it possible to expand the scope of research endeavors and address civic issues without requiring the purchase of specialized sensors or the installation and maintenance of network infrastructure. Data collected using such applications may come from unexpected yet interesting and valuable sources and may allow for collecting data in previously inaccessible locations and contexts. This new data collection paradigm introduces several research challenges. Privacy is a primary concern for users that are contributing sensitive or identifying data. Incentive mechanisms for participation may be needed to encourage people to volunteer their resources to collect data. Methods are needed for processing large-scale, user-generated data sets into meaningful information, and for assessing and understanding the quality of information to help guide decision-making. Approaches that involve the crowd in such data analysis tasks, with humans serving as a source of semantic information, interpretation, and evaluation of crowdsensed/crowdsourced data, can also help to build an understanding of the physical, computational, and socio-technical environment. The CASPer workshop provides a forum for discussion, debate, and collaboration focused on ideas, trends, techniques, and recent advances in crowdsensing/crowdsourcing. We invite original research contributions that advance the state of the art as well as position papers that pose a new direction or present a controversial point of view. CASPer will be held in conjunction with IEEE PerCom 2015 (March 23-27) in St. Louis, Missouri, USA. Accepted papers will be published in the IEEE PerCom Workshop Proceedings.

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重要日期

2014-12-07
摘要截稿日期

征稿范围

Topics of interest include, but are not limited to: Algorithms to handle, process, and visualize large-scale crowdsensing/crowdsourcing data sets Data integrity, security, privacy, and provenance for crowdsensing/crowdsourcing data Determining and assessing Quality of Information for crowdsensing/crowdsourcing data Crowd-assisted (human-in-the-loop) approaches to analyzing crowdsensing/crowdsourcing data Context modeling and reasoning in crowdsensing/crowdsourcing applications Incentive mechanisms for participation in crowdsensing/crowdsourcing applications Supporting crowdsensing/crowdsourcing in heterogeneous networks Crowdsensing/crowdsourcing for pervasive systems Novel use of sensors for crowdsensing/crowdsourcing applications Energy-efficient mechanisms for crowdsensing/crowdsourcing applications Programming abstractions and middleware for crowdsensing/crowdsourcing applications Novel large-scale crowdsensing/crowdsourcing applications
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重要日期
  • 03月23日

    2015

    会议日期

  • 12月07日 2014

    摘要截稿日期

  • 03月23日 2015

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