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.

Abstract. 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. However, in order to interpret the readings from the sensors, the data needs to be put in context through correlation with other sensor readings, sensor data histories, and stored data, as well as juxtaposing with maps and forecast models. In this paper we use a flood emergency response planning application to identify requirements for a semantic sensor web. We propose a generic service architecture to satisfy the requirements that uses semantic annotations to support well-informed interactions between the services. We present the SemSorGrid4Env realisation of the architecture and illustrate its capabilities in the context of the example application.

Abstract

Abstract-Sensor networks are often deployed with the purpose of providing data to large-scale information management and GIS systems, or to collect measurements for specific scientific experiments. The benefits of such use are clear and widely accepted. The reuse of observations in low-cost, lightweight, web applications and mashups is a further compelling use case for sensor networks, but requires provision of data through simple mechanisms, readily accessible, that are quick to develop with. To enable the latter while maintaining support for larger applications and, to increase information utility, links to and from other datasets, we propose a domain-driven approach that embodies REST and Linked Data principles using a common semantic framework that underpins a separation of concerns between domain models, sensor observation infrastructure, and Application Programming Interfaces (APIs) while maintaining information consistency. We describe a reusable, reconfigurable, web service that realises this design and can be deployed to provide access to multiple sources of sensor information, including databases and streaming data, with flexible semantic configuration of the API and domain mapping.

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