Using the Sensor Web to Detect and Monitor the Spread of Vegetation Fires in Southern Africa

Terhorst, Andrew; Moodley, Deshendran; Simonis, Ingo; Frost, Philip; McFerren, Graeme; Roos, Stacey; Bergh, F. van den

doi:10.1007/978-3-540-79996-2_13

Cited by 14 publications

(14 citation statements)

References 11 publications

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“…The Advanced Fire Information System (AFIS) project [ 110 ] combines in-situ measured sensor data (e.g., from weather stations) and remote sensing data to detect wild fires in South Africa. As soon as the power supply infrastructure (power lines or pylons) is endangered, an automatic notification of responsible persons is triggered so that damage to transformers can be prevented.…”

Section: Applying Swementioning

confidence: 99%

New Generation Sensor Web Enablement

Bröring

Echterhoff²,

Jirka

et al. 2011

Sensors

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388

254

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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.

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Section: Applying Swementioning

confidence: 99%

New Generation Sensor Web Enablement

Bröring

Echterhoff²,

Jirka

et al. 2011

Sensors

Self Cite

388

254

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“…The SWAP has three layers: sensor layer, knowledge layer and application layer with ontologies and workflows embedded in the layers when needed. A wild fire monitoring application [36] has used the SWAP for its implementation. Although our SNaaS framework does not use any multi-agent system, it is our interest in the future to also explore such integration.…”

Section: "Semantic Sensor Network" "Semantic Sensor Web" and Ontolmentioning

confidence: 99%

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

Liu

Hill

Rodríguez

et al. 2009

2009 International Symposium on Collaborative Technologies and Systems

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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.

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“…The study [37] introduces a framework for web-based sensor discovery, wherein SensorML is adopted as the model for describing sensor information. SensorML-based information description frameworks have been used in various applications [3], such as the EU directive INSPIRE (http://www.ec-gis.org/inspire/), EU-funded projects SANY (http://sany-ip.eu) and OSIRIS (http://www.osiris-fp6.eu), South Africa AFIS project [38], and US OOSTethys community project (http://www.oostethys.org). Foerster et al [14] state that integrating the sensor information into sensor web environments assists in accessing deployed sensors.…”

Section: Introductionmentioning

confidence: 99%

An Object Model for Integrating Diverse Remote Sensing Satellite Sensors: A Case Study of Union Operation

Chen

et al. 2014

Remote Sensing

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Abstract:In the Earth Observation sensor web environment, the rapid, accurate, and unified discovery of diverse remote sensing satellite sensors, and their association to yield an integrated solution for a comprehensive response to specific emergency tasks pose considerable challenges. In this study, we propose a remote sensing satellite sensor object model, based on the object-oriented paradigm and the Open Geospatial Consortium Sensor Model Language. The proposed model comprises a set of sensor resource objects. Each object consists of identification, state of resource attribute, and resource method. We implement the proposed attribute state description by applying it to different remote sensors. A real application, involving the observation of floods at the Yangtze River in China, is undertaken. Results indicate that the sensor inquirer can accurately discover qualified satellite sensors in an accurate and unified manner. By implementing the proposed union operation among the retrieved sensors, the inquirer can further determine how the selected sensors can collaboratively complete a specific observation requirement. Therefore, the proposed model provides a reliable foundation for sharing and integrating multiple remote sensing satellite sensors and their observations.

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Using the Sensor Web to Detect and Monitor the Spread of Vegetation Fires in Southern Africa

Cited by 14 publications

References 11 publications

New Generation Sensor Web Enablement

New Generation Sensor Web Enablement

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

An Object Model for Integrating Diverse Remote Sensing Satellite Sensors: A Case Study of Union Operation

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