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The application of blockchain technology in data trading: a systematic review. [PDF]
PeerJ Comput SciXiong W, Shao H, Ge H.
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Characterizing smartphone capabilities for seismic and structural monitoring. [PDF]
Sci RepVezio P +3 more
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Incentivization for Health Crowdsensing
2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), 2017Crowdsensing in the case of health-related information can enable a new mode of health data collection, able to collect more detailed and real-world health and physiological data than possible via traditional means. Various incentivization schemes for crowdsensing in general have been proposed, but there are characteristics specific to the health ...
Luis Gabriel Jaimes, Robert Steele
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Jump-start crowdsensing: A three-layer incentive framework for mobile crowdsensing
2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS), 2017In the past decade, with the rapid development of wireless communication and sensor technology, ubiquitous smartphones equipped with increasingly rich sensors have more powerful computing and sensing abilities. Thus, mobile crowdsensing has received extensive attentions from both industry and academia.
Yatong Chen +4 more
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Browser-enabled distributed crowdsensing
2017 4th Experiment@International Conference (exp.at'17), 2017Mobile Crowdsensing is often used for involving large number of persons in distributed sensing experiments. In some cases, (e.g., online games, online sensing of sensitive data, etc.) privacy and security issues arise. Peer-to-peer networks can be effectively used to guarantee anonymity and solve the above mentioned issues.
Bochicchio, Mario A. +4 more
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Crowdsensing in the Wild with Aliens and Micropayments
IEEE Pervasive Computing, 2016This article presents results and lessons learned from two user studies on crowdsensing incentives--specifically, on mobile gaming and micropayments. The analysis of the results suggests that gaming is a cost-effective solution for uniform area coverage, whereas micropayments work well for sensing tasks with tight time constraints or for long-term ...
Manoop Talasila +2 more
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FlySensing: A case for crowdsensing in the air
2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), 2014The volume of commercial flights and the number of passengers carrying one or more digital devices aboard presents an opportunity for innovative research for the application of crowdsensing in the air. This paper explores opportunities to leverage crowdsensing in the context of the commercial airline industry.
Osarieme Omokaro, Jamie Payton
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Posted pricing for robust crowdsensing
Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2016Mobile crowdsensing has been considered as a promising approach for large scale urban data collection, but has also posed new challenging problems such as incentivization and quality control. Among the other incentivization approaches, posted pricing has been widely adopted by commercial systems due to the reason that it naturally achieves truthfulness
Kai Han 0003 +2 more
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Density-aware compressive crowdsensing
Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2017Crowdsensing systems collect large-scale sensor data from mobile devices to provide a wide-area view of phenomena including traffic, noise and air pollution. Because such data often exhibits sparse structure, it is natural to apply compressive sensing (CS) for data sampling and recovery.
Xiaohong Hao +4 more
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Crowdsensing sub-populations in a region
Journal of Ambient Intelligence and Humanized Computing, 2018Crowdsensing refers to an approach for collecting of data from a large number of smart devices and sensors carried by many individuals and has been employed for numerous applications, which include pollution monitoring, traffic monitoring and noise sensing.
Robert Steele, Luis Gabriel Jaimes
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