Real-time geospatial information is used in various applications such as risk management or alerting ***,the rise of new sensing technologies also increases the demand for processing the data in real ***’s spatial da...
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Real-time geospatial information is used in various applications such as risk management or alerting ***,the rise of new sensing technologies also increases the demand for processing the data in real ***’s spatial data infrastructures,however,do not meet the requirements for real-time *** OpenGIS®Web Processing Service(WPS)is not designed to process real-time *** has some major drawbacks in asynchronous processing and cannot handle(geo)data streams out of the *** previous papers,we introduced the geoPipes approach to share spatiotemporal data in real *** implemented the concept extending the Message Queue and Telemetry Transport(MQTT)protocol by a spatial and temporal dimension,which we call *** this paper,we demonstrate the integration of the geoPipes idea in the WPS interface to expose standardized real-time geoprocessing *** proof of the concept is illustrated in some exemplary real-time geo processes.
Artificial hydraulic structures like dams or dikes used for water level regulations or flood prevention are continuously under the influence of the weather and variable river regimes. Thus, ongoing monitoring and simu...
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Artificial hydraulic structures like dams or dikes used for water level regulations or flood prevention are continuously under the influence of the weather and variable river regimes. Thus, ongoing monitoring and simulation is crucial in order to determine the inner condition. Potentially life-threatening situations, in extreme case a failure, must be counteracted by all available means. Nowadays flood warning systems rely exclusively on water level forecast without considering the state of the structure itself. Area-covering continuous knowledge of the inner state including time dependent changes increases the capability of recognizing and locating vulnerable spots for early treatment. In case of a predicted breach, advance warning time for alerting affected citizens can be extended. Our approach is composed of smart sensors integrated in a service-oriented geospatial architecture to monitor and simulate artificial hydraulic structures continuously. The sensors observe the inner state of the construction like the soil moisture or the stress and deformation over time but also various external influences like water levels or wind speed. They are interconnected in distributed network architecture by a so-called sensor bus system based on lightweight protocols like Message Queue Telemetry Transport for Sensor Networks (MQTT-SN). These sensor data streams are transferred into an OGC Sensor Web Enablement (SWE) data structure providing high-level geo web services to end users. Bundled with 3rd party geo web services (WMS etc.) powerful processing and simulation tools can be invoked using the Web Processing Service (WPS) standard. Results will be visualized in a geoportal allowing user access to all information.
Automatic real-time localization of people inside buildings is a huge challenge. For demanding applications in building services, different sensors (e.g. WLAN, RFID, UWB, or ultrasound) are currently used for the real...
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Automatic real-time localization of people inside buildings is a huge challenge. For demanding applications in building services, different sensors (e.g. WLAN, RFID, UWB, or ultrasound) are currently used for the real-time indoor positioning. Most systems are only suitable for specific applications or are used under certain conditions, e.g. additional infrastructures and/or sensory mechanisms are needed. Smartphones, as widespread low-cost multi sensor systems, seem to be a promising platform for mass-market indoor localization applications. In this paper we present an approach for a smartphone-based pedestrian positioning inside of buildings. The novelty of this approach refers to further investigations towards a robust smartphone-based 2.5D pedestrian localization inside of buildings. Therefore, comprehensive analyses concerning barometric height estimations were carried out to expand the predominant 2D position into the third dimension. The 2D position is estimated according to the principle of dead reckoning. Furthermore an extended algorithm based on Sequential Monte Carlo methods for sensor fusion is presented which also integrates building models and a magnetic indoor positioning system.
Artificial hydraulic structures like dams or dikes used for water level regulations or flood prevention are continuously under the influence of the weather and variable river regimes. Thus, ongoing monitoring and simu...
Artificial hydraulic structures like dams or dikes used for water level regulations or flood prevention are continuously under the influence of the weather and variable river regimes. Thus, ongoing monitoring and simulation is crucial in order to determine the inner condition. Potentially life-threatening situations, in extreme case a failure, must be counteracted by all available means. Nowadays flood warning systems rely exclusively on water level forecast without considering the state of the structure itself. Area-covering continuous knowledge of the inner state including time dependent changes increases the capability of recognizing and locating vulnerable spots for early treatment. In case of a predicted breach, advance warning time for alerting affected citizens can be extended. Our approach is composed of smart sensors integrated in a service-oriented geospatial architecture to monitor and simulate artificial hydraulic structures continuously. The sensors observe the inner state of the construction like the soil moisture or the stress and deformation over time but also various external influences like water levels or wind speed. They are interconnected in distributed network architecture by a so-called sensor bus system based on lightweight protocols like Message Queue Telemetry Transport for Sensor Networks (MQTT-SN). These sensor data streams are transferred into an OGC Sensor Web Enablement (SWE) data structure providing high-level geo web services to end users. Bundled with 3rd party geo web services (WMS etc.) powerful processing and simulation tools can be invoked using the Web Processing Service (WPS) standard. Results will be visualized in a geoportal allowing user access to all information.
This paper deals with a real-time capable accurate 3D ultra-wideband radar imaging algorithm for complex shaped 3D objects including edges and corners. A well known wavefront based imaging algorithm is adapted to the ...
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This paper deals with a real-time capable accurate 3D ultra-wideband radar imaging algorithm for complex shaped 3D objects including edges and corners. A well known wavefront based imaging algorithm is adapted to the bi-static 3D scenario which is, in contrast to the popular migration based algorithms, real-time capable and directly gathers the object contour coordinates. In order to reconstruct a accurate 3D object contour, the commonly proposed planar scan track (i.e. the planar aperture) of the antennas is modified and extended to a spatial scanning track with a circumnavigation of the object. To provide a more diverse radar signature the monostatic antenna configuration is extended to a bistatic configuration. Hence, the shape of the radiating wavefront is no longer spherical but ellipsoidal. Consequently, to ensure the super-resolution accuracy, the intersection point of 3 arbitrarily oriented and shifted ellipsoids in the 3 dimensional Euclidean space has to be determined. An iterative solution will be presented which utilizes the Gauss-Newton method to obtain a fast converging estimation with negligible error in the least-square sense. An experimental validation is carried out based on complex test objects with small shape variations relative to the used wavelength, an pseudo noise radar device (from 4.5 GHz to 13.5 GHz) and two tapered slot line Vivaldi antennas.
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