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) |
| 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 |
| Externí odkaz: |
|