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Tackling the Redundancy and Sparsity in Crowd Sensing Applications
- Source :
- SenSys
- Publication Year :
- 2016
- Publisher :
- ACM, 2016.
-
Abstract
- Driven by the proliferation of sensor-rich mobile devices, crowd sensing has emerged as a new paradigm of gathering information about the physical world. In crowd sensing applications, user observations are usually unevenly distributed across the monitored entities, and this gives rise to two major challenges -- redundancy and sparsity. On one hand, multiple users may observe the same entity, and their observations are sometimes conflicting with each other due to the unreliable nature of human-carried sensors. On the other hand, crowd sensing data are usually very sparse, and there may exist considerable number of entities that never receive any observations from users. Some existing work studies these two challenges separately. However, we can gain great benefits by dealing with them jointly. In this paper, we develop an integrated framework to estimate the true values of entities from redundant and sparse data in crowd sensing applications. In this framework, we propose an effective algorithm to infer the "missing" observations for each entity, and aggregate both user-contributed and inferred observations to discover the true values of entities. We conduct extensive experiments on real-world crowd sensing systems to demonstrate the advantages of the proposed framework on correctly inferring entity truths from redundant and sparse data.
- Subjects :
- Sensing applications
Computer science
business.industry
Aggregate (data warehouse)
020206 networking & telecommunications
02 engineering and technology
computer.software_genre
Machine learning
Matrix decomposition
Effective algorithm
Sensing data
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Redundancy (engineering)
Data mining
Artificial intelligence
business
computer
Mobile device
Sparse matrix
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM
- Accession number :
- edsair.doi...........f1a3ad737ca313a09b280d83f27dc583