GOOSE: semantic search on internet connected sensors

Sensor Web researchers are currently investigating middleware to aid in the dynamic discovery, integration and analysis of vast quantities of high quality, but distributed and heterogeneous earth observation data. Key challenges being investigated include dynamic data integration and analysis, service discovery and semantic interoperability. However, few efforts deal with the management of both knowledge and system dynamism. Two emerging technologies that have shown promise in dealing with these issues are ontologies and software agents. This paper introduces the idea and identifies key requirements for a Knowledge Driven Sensor Web and presents our efforts towards developing an associated semantic infrastructure within the Sensor Web Agent Platform.

Semantic Web, 2010

The combination of sensor networks with the Web, web services and database technologies, was named some years ago as the Sensor Web or the Sensor Internet. Most efforts in this area focused on the provision of platforms that could be used to build sensor-based applications more efficiently, considering some of the most important challenges in sensor-based data management and sensor network configuration. The introduction of semantics into these platforms provides the opportunity of going a step forward into the understanding, management and use of sensor-based data sources, and this is a topic being explored by ongoing initiatives. In this paper we go through some of the most relevant challenges of the current Sensor Web, and describe some ongoing work and open opportunities for the introduction of semantics in this context.

Sensors, 2011

Environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent over the past years. As consequence of these technological advancements, sensors are increasingly deployed to monitor our environment. The large variety of available sensor types with often incompatible protocols complicates the integration of sensors into observing systems. The standardized Web service interfaces and data encodings defined within OGC's Sensor Web Enablement (SWE) framework make sensors available over the Web and hide the heterogeneous sensor protocols from applications. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The driver software which enables access to sensors has to be implemented and the measured sensor data has to be manually mapped to the SWE models. In this article we introduce a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) semantic matchmaking functionality, (2) a publish/subscribe mechanism underlying the Sensor Web, as well as (3) a model for the declarative description of sensor interfaces which serves as a generic driver mechanism. We implement and evaluate our approach by applying it to an oil spill scenario. The matchmaking is realized using Sensors 2011, 11 7569 existing ontologies and reasoning engines and provides a strong case for the semantic integration capabilities provided by Semantic Web research.

We describe a prototype ontology-driven information system (ODIS) that exploits what we call Portion of Reality (POR) representations. The system takes both sensor data and natural language text as inputs and composes on this basis logically structured POR assertions. The goal of our prototype is to represent both natural language and sensor data within a single framework that, in addition to axiomatic reasoning, directly supports computations and is capable of discovering and representing new kinds of situations and thematic roles, (e.g., roles such as agent, patient and instrument), based on new compositions of existing representations. We applied our prototype in an intelligence analysis use case to test the hypothesis that a framework of this sort can produce usefully structured information from combined natural language and sensor data inputs. We further tested our hypothesis by adding an enhanced US Air Force ontology framework to our ODIS in order to (1) process a collection of sensor data, intel reports, and mission plans; (2) build composite POR representations from these data; and (3) machine analyze the fused results to infer mission threats.

2006

Semantic technologies are often proposed as important components of complex, cross-jurisdictional, heterogeneous, dynamic information systems. The needs and opportunities arising from the rapidly growing capabilities of networked sensing devices are a challenging case. It is estimated that today there are 4 billion mobile devices that can act as sensors, including active and passive RFID tags. This is complemented by an even larger number of fixed sensors recording observations of a wide variety of modalities.

Semantic technologies are often proposed as important components of complex, cross-jurisdictional, heterogeneous, dynamic information systems. The needs and opportunities arising from the rapidly growing capabilities of networked sensing devices are a challenging case. It is estimated that today there are 4 billion mobile devices that can act as sensors, including active and passive RFID tags. This is complemented by an even larger number of fixed sensors recording observations of a wide variety of modalities.

2011

Abstract. Main restraints curbing a deep integration of Semantic Sensor Networks with complex and articulated architectures, basically reside in too elementary allowed discovery capabilities. Several studies agree advanced querying and retrieval mechanisms are needed to truly fulfill the potential of the SSN paradigm. This paper presents a novel SSN framework, supporting a resource discovery grounded on semantic-based matchmaking.

lenvis.eu

The quick development and deployment of sensor technology within the general frame of the Internet of Things poses relevant opportunity and challenges. The sensor is not a pure data source, but an entity (Semantic Sensor Web) with associated metadata and it is a building block of a "worldwide distributed" real time database, to be processed through real-time queries. Important challenges are to achieve interoperability in connectivity and processing capabilities (queries) and to apply "intelligence" and processing capabilities as close as possible to the source of data. This paper presents the extension of a general architecture for data integration in which we add capabilities for processing of complex queries and discuss how they can be adapted to, and used by, an application in the Semantic Sensor Web, presenting a pilot study in environment and health domains. 1 LENVIS -Localised environmental and health information services for all.

2012

ABSTRACT User queries are becoming increasingly local where people are interested in what their friends are up to or what is happening in their local area. Sensors can assist in localised information retrieval by giving the search engine direct access to events happening in the local world. In this paper, we describe an open source framework to search in realtime multimedia and social streams.