Multiple Spatial Model Fusion in Heterogeneous Sensor Networks

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, the 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.