A Hybrid Approach for Improving the Data Quality of Mobile Phone Sensing

Few studies have researched the temporal and spatial effects of insufficient exposure of sensors in mobile phone sensing. In this paper, the missing data problem in mobile phone sensing is addressed by using a hybrid approach to design an estimation model. This estimation model reflects the effects of participatory and opportunistic nodes based on the success probability model. The proposed model considers the spatial and temporal correlation of sensing data to accurately estimate the missing information. By applying the linear regression and linear interpolation models to sample data from neighboring nodes of the missing data, the spatial and temporal context can be described. The experiment results show that the proposed model can estimate the missing data accurately in terms of simulated and real-world datasets.

• Publication year

  2013

• Venue

  Int. J. Distributed Sens. Networks

• Publication date

  2013-04-01

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1155/2013/786594
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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