The Second Workshop on Mobile Crowdsensing Systems and Applications will be held in conjunction with the IEEE International Conference on Mobile Ad-Hoc and Smart Systems (IEEE MASS 2019) in Monterey, CA, USA

The Workshop Scope:

With the rapid development of wireless communication and sensor technology, ubiquitous mobile devices equipped with increasingly rich sensors have more powerful computing and sensing abilities. Mobile crowdsensing (MCS), as a special form of crowdsourcing where communities contribute sensing information and human intelligence using mobile devices to form a body of knowledge, has received extensive attentions from both academia and industry. Various MCS applications come forth, such as indoor positioning, environment monitoring, and transportation, etc. MCS spans a wide spectrum of user involvement, from collecting sensor measurements with no user intervention to requiring active participation of mobile users. Despite the growing interest and some commercial success in MCS, MCS still faces significant challenges such as motivation and incentives, low data quality (incomplete data, noisy data, redundant data, etc.), privacy, security and data integrity, localized analytics, resource limitations, context-awareness, sensing resource management, aggregate analytics, and public safety, etc. This workshop aims to bring together researchers in the field of mobile crowdsensing to exchange ideas and advance the research frontier. We invite submissions in the following non-exclusive list of topics:

Topics of Interest (but not limited to):

• Mobile crowdsensing frameworks, platforms and systems
• Mobile crowdsensing applications and case study
• Mobile crowdsensing, participatory and opportunistic sensing and data collection
• Design and analysis of sensing scheduling algorithms in mobile crowdsensing
• Sensing resource management in mobile crowdsensing
• Mobile crowdsensing data communication and sharing
• Incentive mechanism and economic systems for mobile crowdsensing
• Distributed and parallel algorithms for processing big crowd sensed data in mobile crowdsensing
• Big crowd sensed data processing, storage and mining
• Machine learning and data mining algorithms and applications for sensed data in mobile crowdsensing
• Architecture and framework for management of crowd sensed data in mobile crowdsensing
• Human centric data management and analytics models in mobile crowdsensing
• Big data spatial-temporal analysis in mobile crowdsensing
• Data quality and pricing in mobile crowdsensing
• Security, data privacy preservation, and trust management in mobile crowdsensing
• Location and mobility prediction and inference
• Social networks in mobile crowdsensing
• Mobile crowdsensing with IoT for smart cities and ecology
• Novel mobile crowdsensing and human centric data management applications

Important Dates:

Paper Submission Deadline: September 27, 2019 (Anywhere on Earth)

Notification of Acceptance: October 8, 2019

Camera-ready Version: October 15, 2019 (Firm Deadline)