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Memorias de investigación
Communications at congresses:
Deriving Semantic Sensor Metadata from Raw Measurements
Year:2012
Research Areas
  • Information technology and adata processing
Information
Abstract
Sensor network deployments have become a primary source of big data about the real world that surrounds us, measuring a wide range of physical properties in real time. With such large amounts of heterogeneous data, a key challenge is to describe and annotate sensor data with high-level metadata, using and extending models, for instance with ontologies. However, to automate this task there is a need for enriching the sensor metadata using the actual observed measurements and extracting useful meta-information from them. This paper proposes a novel approach of characterization and extraction of semantic metadata through the analysis of sensor data raw observations. This approach consists in using approximations to represent the raw sensor measurements, based on distributions of the observation slopes, building a classi?cation scheme to automatically infer sensor metadata like the type of observed property, integrating the semantic analysis results with existing sensor networks metadata.
International
Si
Congress
ISWC2012 5th International Workshop on Semantic Sensor Networks 2011 (SSN2012)
960
Place
Boston (Estados Unidos)
Reviewers
Si
ISBN/ISSN
1613-0073
Start Date
10/11/2012
End Date
10/11/2012
From page
33
To page
48
CEUR Workshop Proceedings, Vol-904
Participants
  • Autor: Jean Paul Calbimonte . (UPM)
  • Autor: Oscar Corcho Garcia (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
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