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In recent times, Mobile Crowdsensing has gained a lot of attention and has become a promising platform. It is an approach to collect samples in a particular domain by spreading tasks to be done by individuals. It explores different fields from the point of view of monitoring applications such as social networks, public health, lifestyle, and making the use of sensing and wireless communication capabilities. MCS frameworks include incentives mechanism, task allocation, user selection, path planning, privacy and security concerns, data quality. Despite enhancements throughout the years, MCS solutions need more comprehensive understanding on many aspects. In this paper, we extend MCS research by providing comprehensive understanding of MCS as a sensing paradigm and discusses the existing works with focus on Incentive Mechanism and Path Planning Algorithm. Our aim is to analyze and integrate existing research while identifying future directions in incentive mechanisms and path planning.

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A Joint Survey on Incentives Mechanisms and Path Planning Algorithms in Mobile Crowdsensing System

  • 会议论文

  • 发表日期：

    2026年

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  • Ananya Mishra,
  • Himanshi Garg,
  • Drishti Anand,
  • Vivekanand Jha,
  • Deepika Suhag

摘要

In recent times, Mobile Crowdsensing has gained a lot of attention and has become a promising platform. It is an approach to collect samples in a particular domain by spreading tasks to be done by individuals. It explores different fields from the point of view of monitoring applications such as social networks, public health, lifestyle, and making the use of sensing and wireless communication capabilities. MCS frameworks include incentives mechanism, task allocation, user selection, path planning, privacy and security concerns, data quality. Despite enhancements throughout the years, MCS solutions need more comprehensive understanding on many aspects. In this paper, we extend MCS research by providing comprehensive understanding of MCS as a sensing paradigm and discusses the existing works with focus on Incentive Mechanism and Path Planning Algorithm. Our aim is to analyze and integrate existing research while identifying future directions in incentive mechanisms and path planning.