A semantic sensor web for environmental decision support applications

Autor: Raúl García-Castro, Alasdair J. G. Gray, Alex Frazer, Norman W. Paton, Jason Sadler, Jean-Paul Calbimonte, Ixent Galpin, Kostis Kyzirakos, Manos Karpathiotakis, David De Roure, Kevin R. Page, Asunción Gómez-Pérez, Oles Kit, Oscar Corcho, Manolis Koubarakis, Alvaro A. A. Fernandes, Kirk Martinez
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Web standards
Decision support system
medicine.medical_specialty
Computer science
02 engineering and technology
lcsh:Chemical technology
computer.software_genre
Biochemistry
Social Semantic Web
Article
Analytical Chemistry
Decision Support Techniques
World Wide Web
application and visualisation
020204 information systems
Semantic computing
semantic sensor web
0202 electrical engineering
electronic engineering
information engineering
Semantic analytics
medicine
Web application
lcsh:TP1-1185
semantic data integration
Electrical and Electronic Engineering
Human resources
Instrumentation
Data Web
Informática
business.industry
Linked data
Atomic and Molecular Physics
and Optics
Sensor web
Semantic grid
13. Climate action
Semantic Sensor Web
Semantic technology
020201 artificial intelligence & image processing
Web service
business
Web intelligence
Wireless sensor network
computer
Web modeling
Environmental Monitoring
Zdroj: Sensors; Volume 11; Issue 9; Pages: 8855-8887
Sensors, ISSN 1424-8220, 2011-09-14, Vol. 11, No. 9
Archivo Digital UPM
Universidad Politécnica de Madrid
Sensors (Basel, Switzerland)
Sensors, Vol 11, Iss 9, Pp 8855-8887 (2011)
DOI: 10.3390/s110908855
Popis: 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.
Databáze: OpenAIRE
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