Many sensor networks have been deployed to monitor Earth’s environment, and more will follow in the future. Environmental sensors have improved continuously by becoming smaller, cheaper, and more intelligent. Due to the large number of sensor manufacturers and differing accompanying protocols, integrating diverse sensors into observation systems is not straightforward. A coherent infrastructure is needed to treat sensors in an interoperable, platform-independent and uniform way. The concept of the Sensor Web reflects such a kind of infrastructure for sharing, finding, and accessing sensors and their data across different applications. It hides the heterogeneous sensor hardware and communication protocols from the applications built on top of it. The Sensor Web Enablement initiative of the Open Geospatial Consortium standardizes web service interfaces and data encodings which can be used as building blocks for a Sensor Web. This article illustrates and analyzes the recent developments of the new generation of the Sensor Web Enablement specification framework. Further, we relate the Sensor Web to other emerging concepts such as the Web of Things and point out challenges and resulting future work topics for research on Sensor Web Enablement.
An ever-increasing number of sensor resources are being exposed via the World Wide Web to become part of the Digital Earth. Discovery, selection and use of these sensors and their observations require a robust sensor information model, but the consistent description of sensor metadata is a complex and difficult task. Currently, the only available robust model is SensorML, which is intentionally designed in a very generic way. Due to this genericness, interoperability can hardly be achieved without the definition of application profiles that further constrain the use and expressiveness of the root language. So far, such SensorML profiles have only been developed up to a limited extent. This work describes a new approach for defining sensor metadata, the Starfish Fungus Language (StarFL) model. This language follows a more restrictive approach and incorporates concepts from the recently published Semantic Sensor Network Ontology to overcome the key issues users are experiencing with SensorML. StarFL defines a restricted vocabulary and model for sensor metadata to achieve a high level of interoperability and a straightforward reusability of sensor descriptions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.