CarTel: a distributed mobile sensor computing system
Proceedings of the 4th international conference on Embedded networked sensor systems
Virtual trip lines for distributed privacy-preserving traffic monitoring
Proceedings of the 6th international conference on Mobile systems, applications, and services
Micro-Blog: sharing and querying content through mobile phones and social participation
Proceedings of the 6th international conference on Mobile systems, applications, and services
Automatic Collection of Fuel Prices from a Network of Mobile Cameras
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
Nericell: rich monitoring of road and traffic conditions using mobile smartphones
Proceedings of the 6th ACM conference on Embedded network sensor systems
LiveCompare: grocery bargain hunting through participatory sensing
Proceedings of the 10th workshop on Mobile Computing Systems and Applications
Mobile Broadband - Including WiMAX and LTE
Mobile Broadband - Including WiMAX and LTE
A crowdsourceable QoE evaluation framework for multimedia content
MM '09 Proceedings of the 17th ACM international conference on Multimedia
SMILE: encounter-based trust for mobile social services
Proceedings of the 16th ACM conference on Computer and communications security
Corroborating information from disagreeing views
Proceedings of the third ACM international conference on Web search and data mining
Toward trustworthy mobile sensing
Proceedings of the Eleventh Workshop on Mobile Computing Systems & Applications
Quality management on Amazon Mechanical Turk
Proceedings of the ACM SIGKDD Workshop on Human Computation
Towards trustworthy participatory sensing
HotSec'09 Proceedings of the 4th USENIX conference on Hot topics in security
The Journal of Machine Learning Research
Location-based crowdsourcing: extending crowdsourcing to the real world
Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries
CrowdDB: answering queries with crowdsourcing
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Quality control for real-time ubiquitous crowdsourcing
Proceedings of the 2nd international workshop on Ubiquitous crowdsouring
Proceedings of the VLDB Endowment
Answering search queries with CrowdSearcher
Proceedings of the 21st international conference on World Wide Web
CrowdScreen: algorithms for filtering data with humans
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
CDAS: a crowdsourcing data analytics system
Proceedings of the VLDB Endowment
Learning from crowds in the presence of schools of thought
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
CrowdER: crowdsourcing entity resolution
Proceedings of the VLDB Endowment
Whom to ask?: jury selection for decision making tasks on micro-blog services
Proceedings of the VLDB Endowment
GeoCrowd: enabling query answering with spatial crowdsourcing
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
CrowdSeed: query processing on microblogs
Proceedings of the 16th International Conference on Extending Database Technology
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Many studies foresee significant future growth in the number of mobile smart phone users, the phone's hardware and software features, and the broadband bandwidth. Therefore, a transformative area of research is to fully utilize this new platform for various tasks, among which the most promising is spatial crowdsourcing. Spatial crowdsourcing (SC) engages individuals, groups, and communities in the act of collecting, analyzing, and disseminating urban, social, and other spatiotemporal information. This new paradigm of data collection has shown to be useful when traditional means fail (e.g., due to disaster), are censored or do not scale in time and space. Two major impediments to the success of spatial crowdsourcing in real-world applications are scalability and trust issues. Without scale considerations, it is impossible to develop a generic multi-campaign spatial crowdsourcing system (SC-system) that can efficiently and in real-time match many requesters' tasks to numerous workers. Without trust, the SC-system cannot evaluate the credibility of the contributed data, rendering it ineffective for replacing the traditional data collection means. In this paper, we survey and study both issues of scale and trust in spatial crowdsourcing.