Monitoring moving objects using uncertain web data

  • Mouhamadou Lamine
  • , Ba Sébastien Montenez
  • , Talel Abdessalem
  • , Pierre Senellart

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A number of applications deal with monitoring moving objects: cars, aircrafts, ships, persons, etc. Traditionally, this requires capturing data from sensor networks, image or video analysis, or using other application-specific resources. We show in this demonstration paper howWeb content can be exploited instead to gather information (tra-jectories, metadata) about moving objects. As this content is marred with uncertainty and inconsistency, we develop a methodology for estimating uncertainty and filtering the resulting data. We present as an application a demonstration of a system that constructs tra-jectories of ships from social networking data, presenting to a user inferred trajectories, meta-information, as well as uncertainty levels on extracted information and trustworthiness of data providers.

Original languageEnglish
Title of host publication22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2014
EditorsMarkus Schneider, Michael Gertz, Yan Huang, Jagan Sankaranarayanan, John Krumm
PublisherAssociation for Computing Machinery
Pages565-568
Number of pages4
ISBN (Electronic)9781450331319
DOIs
Publication statusPublished - 4 Nov 2014
Externally publishedYes
Event22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2014 - Dallas, United States
Duration: 4 Nov 20147 Nov 2014

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
Volume04-07-November-2014

Conference

Conference22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2014
Country/TerritoryUnited States
CityDallas
Period4/11/147/11/14

Keywords

  • Moving Objects
  • Social Web Data
  • Trajectory
  • Uncertainty Estimation

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