In recent years the fusion of multimedia information from multiple real-time sources and databases has become increasingly important because of its practical significance in many application areas such as telemedicine, community networks for crime prevention, health care, emergency management, e-learning, digital library, and field computing for scientific exploration. To support the retrieval and fusion of multimedia information from multiple real-time sources and databases, a novel approach

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... r sensor-based query processing is described. Since most sensors can generate large quantities of spatial information within short periods of time, sensor-based query processing requires new techniques for query optimization. The sensor dependency tree is used to facilitate query optimization. Through query refinement one or more sensor may provide feedback information to the other sensors. The approach is also applicable to evolutionary queries that change in time and/or space, depending upon the temporal/spatial coordinates of the query originator. It provides significant improvements in the accuracy and efficiency in multi-sensor information fusion and accomplishes sensor data independence through the construction of an ontological knowledge base.