SIMLAug 3, 2015

When Crowdsourcing Meets Mobile Sensing: A Social Network Perspective

arXiv:1508.00299v138 citations
Originality Synthesis-oriented
AI Analysis

This work addresses mobile sensing challenges by leveraging social networks for trust, though it appears incremental in combining existing crowdsourcing and mobile sensing approaches.

The paper tackles the problem of improving mobile sensing performance by integrating crowdsourcing methods with social network-inspired trust mechanisms, demonstrating improved performance through numerical experiments on real-world datasets.

Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigates the structure of mobile sensing schemes and introduces crowdsourcing methods for mobile sensing. Inspired by social network, one can establish trust among participatory agents to leverage the wisdom of crowds for mobile sensing. A prototype of social network inspired mobile multimedia and sensing application is presented for illustrative purpose. Numerical experiments on real-world datasets show improved performance of mobile sensing via crowdsourcing. Challenges for mobile sensing with respect to Internet layers are discussed.

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