Deriving semantic sensor metadata from raw measurements

Calbimonte, JP. and Corcho, Oscar and Yan, Zhixian and Jeung, H. and Aberer, K. (2012). Deriving semantic sensor metadata from raw measurements. In: "5th International Workshop on Semantic Sensor Networks", 10/11/2012 - 10/11/2012, Boston (Estados Unidos). ISBN 1613-0073. pp. 33-48.

Description

Title: Deriving semantic sensor metadata from raw measurements
Author/s:
  • Calbimonte, JP.
  • Corcho, Oscar
  • Yan, Zhixian
  • Jeung, H.
  • Aberer, K.
Item Type: Presentation at Congress or Conference (Article)
Event Title: 5th International Workshop on Semantic Sensor Networks
Event Dates: 10/11/2012 - 10/11/2012
Event Location: Boston (Estados Unidos)
Title of Book: Proceedings of the 5th International Workshop on Semantic Sensor Networks
Date: 2012
ISBN: 1613-0073
Volume: 904
Subjects:
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

More information

Item ID: 20393
DC Identifier: http://oa.upm.es/20393/
OAI Identifier: oai:oa.upm.es:20393
Official URL: http://ceur-ws.org/Vol-904/
Deposited by: Memoria Investigacion
Deposited on: 25 Oct 2013 15:14
Last Modified: 21 Apr 2016 23:09
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