Social-Sensor Cloud Service for Scene Reconstruction

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10601)


We propose a new social-sensor cloud services selection framework for scene reconstruction. The proposed research represents social media data streams, i.e., images’ metadata and related posted information, as social sensor cloud services. The functional and non-functional aspects of social sensor cloud services are abstracted from images’ metadata and related posted information. The proposed framework is a 4-stage algorithm, to select social-sensor cloud services based on the user queries. The selection algorithm is based on spatio-temporal indexing, spatio-temporal and textual correlations, and quality of services. Analytical results are presented to prove the efficiency of the proposed approach in comparison to a traditional approach of image processing.



This research was made possible by DP160103595 grant from Australian Research Council and NPRP 9-224-1-049 grant from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of ScienceRMIT UniversityMelbourneAustralia
  2. 2.School of Information TechnologiesThe University of SydneySydneyAustralia
  3. 3.College of EngineeringQatar UniversityDohaQatar

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