Multiple Spatial Model Fusion in Heterogeneous Sensor Networks

Jiangfan Feng, Wei Wei
<span title="2014-02-28">2014</span> <i title="Science and Engineering Research Support Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gri3ay7vs5efhoridfutfkfagu" style="color: black;">International Journal of Multimedia and Ubiquitous Engineering</a> </i> &nbsp;
With the growth of location-based services (LBS), location-based data is a crucial role for many sensor-network applications. Although the conversion of data formats in heterogeneous sensor networks has been studied extensively, the integration of spatial data models is not well understood, which is important to understand the semantics of spatial data in sensor networks. To determine the spatial data integration in model level, we have investigated the cognitive model of spatial information,
more &raquo; ... e conceptual model of space phenomena, and the logic of spatial data management mode, leading to the integration of various spatial data sets from the view of model integration. Furthermore, we provide a method for the effective storage and management of massive and multi-source heterogeneous spatial data. Ultimately, the experimental result shows that the method offers a better way of model integration that cannot be achieved with existing schemes. powerful object awareness ability of the Internet of things front-end provides the innovative processing model for spatial information application. Secondly, transparent resource accessing characteristic of the Internet of things back-ends offers a unified platform with computing, storage and access for the spatial information application. Although, Internet of things provides an unprecedented opportunity to the spatial data acquisition and management, we must realize clearly the challenges which the entire new framework poses. As an infrastructure, sensors on the internet of things lack effective management, programming, scheduling, collaboration and sharing mechanism, without collaborative incident observing and correlative holistic factors in incident detecting, which only observe incident but not analyze effectively, verify authenticity and predict change tendency for the dynamically changing phenomenon. It is a major challenge facing the spatial information service in Internet of Things environment. Therefore, how to search the corresponding modeling method and integration algorithms in the spatial data model level, with considering of the technology factors of spatial data integration? Generating the semantic information with medium granularity, flexible organization and appropriate expression, it can process the magnitude data and the complex large-scale anonymous application demands immediately, which has customizable pattern recognition ability. On this basis, scale magnitude multi-source heterogeneous spatial data is collected and managed by the Internet of things platform, according to the space information service demand for smart city. And it supports the multidimensional spatial data integration in data model levels, and supports the fusion storage of different types of spatial data including the vector data, grinned data, text and real-time multimedia data, with the purpose of improving the current service ability of digital city and providing the technical storage support for smart city system facing the future.
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