User Characteristic Aware Participant Selection for Mobile Crowdsensing. [PDF]
Sensors (Basel), 2018 Wu D, Li H, Wang R.
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Differentially Private and Skew-Aware Spatial Decompositions for Mobile Crowdsensing. [PDF]
Sensors (Basel), 2018 Kim JS, Chung YD, Kim JW.
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Efficient Path Planning and Truthful Incentive Mechanism Design for Mobile Crowdsensing. [PDF]
Sensors (Basel), 2018 Tao X, Song W.
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PUEGM: A Method of User Revenue Selection Based on a Publisher-User Evolutionary Game Model for Mobile Crowdsensing. [PDF]
Sensors (Basel), 2019 Shao Z, Wang H, Feng G.
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Data collection for mobile crowdsensing in the presence of selfishness. [PDF]
EURASIP J Wirel Commun Netw, 2016 Liu J, Bic L, Gong H, Zhan S.
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Scalable and Cost-Effective Assignment of Mobile Crowdsensing Tasks Based on Profiling Trends and Prediction: The ParticipAct Living Lab Experience. [PDF]
Sensors (Basel), 2015 Bellavista P +3 more
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E-PTES-S: Enhanced Trust Evaluation via Multidimensional Spatiotemporal Fusion and Variance-Based Stability Sequence Extraction in IoT Sensing Networks. [PDF]
Sensors (Basel)Liu J +5 more
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Secure and Trusted Crowdsensing for Outdoor Air Quality Monitoring: State of the Art and Perspectives. [PDF]
Sensors (Basel)Marche C +6 more
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Bridging the Gap: An Algorithmic Framework for Vehicular Crowdsensing. [PDF]
Sensors (Basel)Jaimes LG, White C, Abedin P.
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Pricing Incentive Mechanisms for Medical Data Sharing in the Internet of Things: A Three-Party Stackelberg Game Approach. [PDF]
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