Wireless sensor networks (WSN) generate large volumes of raw data which possess natural heterogeneity. WSNs are normally application specific with no sharing or reusability of sensor data among applications. In order for applications and services to be developed independently of particular WSNs, sensor data need to be enriched with semantic information. In this paper, we propose a semantic Web architecture for sensor networks (SWASN). This information oriented architecture allows the sensor data to be understood and processed in a meaningful way by a variety of applications with different purposes. We develop ontologies for sensor data and use the Jena API for processing which includes querying and inference over sensor data. By studying a building fire emergency scenario, we show that semantic Web technologies can provide high level information extraction and inference of sensor data.

Semantic Sensor Information Description and Processing

Nowadays, many buildings are equipped by Building Automation Systems, which utilize numerous sensors acquiring large amounts of data. Such data is useful to assess the performance of existing building systems and hence to support a variety of decisions made during facility operations and maintenance. However, sensor data alone typically does not support analyses of conditions of a facility since there is a need to understand the context under which data is collected. Therefore, data about sensors, and data collected by sensors and the corresponding spatial contextual information from a building information model are required to be analyzed in an integrated way. Although existing standards provide specifications to represent some aspects of sensor metadata (e.g. SensorML) and building information (e.g. IFC), an approach, which integrates information about sensors and building elements, is still needed. In relation to this, the authors first discuss requirements for a model integrating both sensor metadata and building information and then present possible approaches for developing such a model. The discussions include a synthesis and analyses of existing standards for supporting representation of sensor metadata and building information models, and overview of a prototype implemented to generate integrated models of sensors and building information.

Requirements and Evaluation of Standards for Integration of Sensor Data with Building Information Models

Engineering and Physical Sciences Research Council, Innovate UK (CSIC Innovation and Knowledge Centre (Grant ID: EP/L010917/1))

Management of structural monitoring data of bridges using BIM

How the heterogeneous and distributed atmospheric satellite sensors can achieve precise discovery and collaborative observation is a big challenge. In this study, we propose an atmospheric satellite sensor observation system meta-model that reuses and extends the existing geospatial or sensor-related metadata standards to enable the sharing and interoperability of atmospheric satellite sensors. The Open Geospatial Consortium Sensor Model Language (SensorML) has a clear hierarchy in describing the metadata framework, and it is adopted as the carrier to formalize our proposed meta-model into the Atmospheric Satellite Sensor Observation Information Model (A-SSOIM). Three different types of atmospheric satellite sensors are used to test the versatility of the proposed meta-model and the applicability of this formal expression of A-SSOIM. Results show that the proposed meta-model can be reused in all kinds of atmospheric satellite sensors to enable the sharing of atmospheric satellite sensor information and potentially promoting the interoperability of these satellite sensors.

A Sharable and Interoperable Meta-Model for Atmospheric Satellite Sensors and Observations

This paper describes our first step towards the realization of complex and large scale cross-organization virtual observatories by presenting a new semantically-enhanced “Sensor Network as a Service” (SNaaS) framework, which can repurpose existing sensor networks as needed and aggregate and fuse heterogeneous sensors into new virtual sensors in near-real-time. The architecture of this system allows users to create virtual sensors in a Web 2.0 collaborative map interface. Components of the system are highlighted in the paper including a semantically enhanced streaming data toolkit, virtual sensor ontologies and management middleware. Case studies are presented which can allow users to create new virtual rain gages based on the NEXRAD (Next Generation Weather Radar) data stream with or without in-situ rain gages on demand in a Chicago urban watershed testbed. The resulting virtual sensor data streams then can be published in multiple formats including a SWE-compliant one so that external SWE-compliant users and applications can seamlessly query and integrate them.

A new framework for on-demand virtualization, repurposing and fusion of heterogeneous sensors

Distributed sensor networks are emerging technology for building applications in control and condition monitoring of equipment and machinery in government and industry. Open sensor interfaces, standard sensor data formats, and messaging standards are needed to enable the integration, access, fusion, use, and delivery of sensor-derived data for these applications. The sensor standards harmonization working group was formed at NIST to address these types of issues. This paper examines some relevant open standards that can help to achieve seamless sensor connections, integration, discovery, access, and usage within and across systems, networks, and enterprises through the Web.

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Kang Lee

Papers

Sensor standards harmonization-path to achiewving sensor interoperability