Next Article in Journal
Reconstruction of Self-Sparse 2D NMR Spectra from Undersampled Data in the Indirect Dimension
Previous Article in Journal
Detailed Study of Amplitude Nonlinearity in Piezoresistive Force Sensors
Sensors 2011, 11(9), 8855-8887; doi:10.3390/s110908855

A Semantic Sensor Web for Environmental Decision Support Applications

1,* , 2
, 2,3
, 4
, 4
, 5
, 6
, 5
, 6
, 1
, 1
, 1
, 5
, 4
, 6
, 6
 and 5
1 School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK 2 GeoData Institute, University of Southampton, Southampton SO17 1BJ, UK 3 Department of Climate Impacts and Vulnerabilities, Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, D-14412 Potsdam, Germany 4 Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens 15784, Greece 5 Ontology Engineering Group, Universidad Politécnica de Madrid, Campus de Montegancedo s/n 28660, Boadilla del Monte, Madrid, Spain 6 School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK
* Author to whom correspondence should be addressed.
Received: 26 July 2011 / Revised: 29 August 2011 / Accepted: 29 August 2011 / Published: 14 September 2011
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [2275 KB, uploaded 21 June 2014]   |   Browse Figures


Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.
Keywords: semantic sensor web; application and visualisation; semantic data integration semantic sensor web; application and visualisation; semantic data integration
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Export to BibTeX |

MDPI and ACS Style

Gray, A.J.G.; Sadler, J.; Kit, O.; Kyzirakos, K.; Karpathiotakis, M.; Calbimonte, J.-P.; Page, K.; García-Castro, R.; Frazer, A.; Galpin, I.; Fernandes, A.A.A.; Paton, N.W.; Corcho, O.; Koubarakis, M.; Roure, D.D.; Martinez, K.; Gómez-Pérez, A. A Semantic Sensor Web for Environmental Decision Support Applications. Sensors 2011, 11, 8855-8887.

View more citation formats

Related Articles

Article Metrics


Citing Articles

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert