Crowdsensing is a new paradigm of applications that enables the ubiquitous mobile devices with enhanced sensing capabilities, such as smartphones and wearable devices, to collect and to share local information towards a common goal. Most of the smart devices are equipped with a rich set of cheap and powerful sensors, e.g., accelerometer, digital compass, GPS, microphone, and camera. These sensors can be utilized to monitor mobile users’ surrounding environment, and infer human activities and contexts. In recent years, a wide variety of applications have been developed to realize the potential of crowdsensing throughout everyday life, such as environmental monitoring, noise pollution assessment, road and traffic condition monitoring, road-side parking statistics, and indoor localization. The data acquired through crowdsensing exhibits a number of important characteristics, such as large in scale (Volume), fast speed of generation (Velocity), different in forms (Variety), and uncertain in quality (Veracity). The 4Vs of crowdsensing data make it extremely interesting and challenging in designing participatory and opportunistic sensing technologies, human centric data management and analytics models, and novel visualization tools.
The objective of this workshop is to invite authors to submit original manuscripts that demonstrate and explore current advances in all aspects of big data management in crowdsensing environments. The workshop solicits novel papers on a broad range of topics, including but not limited to:
- Architecture and framework design for crowdsensing
- Theoretic foundations of crowdsensing
- Participatory and opportunistic sensing
- Crowdsensing data communication and sharing
- Algorithm design for sensing scheduling
- Big crowdsensing data processing, storage, and mining
- Sensing resource management in crowdsensing
- Economic systems and incentive mechanisms for crowdsensing
- Security, privacy preservation, and trust management in crowdsensing
- Social and psychological issues in crowdsensing
- Novel applications of crowdsensing
- Experience reports and studies of crowdsensing systems
Extended versions of all the accepted papers will be considered for publishing in Special Issue on Big Data Management for Mobile Crowdsensing of Mobile Information Systems Journal (SCI Indexed, Impact Factor: 1.789).
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