Data fusion plays a major role in assisting decision makers by providing them with an improved si... more Data fusion plays a major role in assisting decision makers by providing them with an improved situational awareness so that informed decisions could be made about the events that occur in the field. This involves combining a multitude of sensor modalities such that the resulting output is better (i.e., more accurate, complete, dependable etc.) than what it would have been if the data streams (hereinafter referred to as ‘feeds’) from the resources are taken individually. However, these feeds lack any context-related information (e.g., detected event, event classification, relationships to other events, etc.). This hinders the fusion process and may result in creating an incorrect picture about the situation. Thus, results in false alarms, waste valuable time/resources.
In this paper, we propose an approach that enriches feeds with semantic attributes so that these feeds have proper meaning. This will assist underlying applications to present analysts with correct feeds for a particular event for fusion. We argue annotated stored feeds will assist in easy retrieval of historical data that may be related to the current fusion. We use a subset of Web Ontology Language (OWL),1 OWL-DL to present a lightweight and efficient knowledge layer for feeds annotation and use rules to capture crucial domain concepts. We discuss a solution architecture and provide a proof-of-concept tool to evaluate the proposed approach. We discuss the importance of such an approach with a set of user cases and show how a tool like the one proposed could assist analysts, planners to make better informed decisions.
The net-centric ISR/ISTAR networks are expected to play a crucial role in the success of critical... more The net-centric ISR/ISTAR networks are expected to play a crucial role in the success of critical tasks such as base perimeter protection, border patrol and so on. To accomplish these tasks in an effective and expedient manner, it is important that these networks have the embedded capabilities to discover, delegate, and gather relevant information in a timely and robust manner. In this paper, we present a system architecture and an implementation that combines a service based reasoning mechanism with a sensor middleware infrastructure so that tasks can be executed efficiently and effectively. A knowledge base, utilising the Semantic Web technologies, provides the foundation for reasoning mechanism that assists users to discover, identify and allocate resources that are made available through the middleware, in order to satisfy the needs of tasks. Once resources are allocated to any given task, they can be accessed, controlled, shared, and their data feeds consumed through the Fabric middleware. We use the semantic descriptions from the knowledge base to annotate the resources (types, capabilities, etc.) in the sensor middleware so that they can be retrieved for reasoning during the discovery and identification phases. The reasoner is implemented as a HTTP web service, with the following characteristics:
1. Computational intensive operations are off-loaded to dedicated nodes, preserving the resources in the ISR/ISTAR networks.
2. HTTP services are accessible through a standard set of APIs irrespective of the reasoner technology used.
3. Support for seamless integration of different reasoners into the system.
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Papers by Geeth De Mel
In this paper, we propose an approach that enriches feeds with semantic attributes so that these feeds have proper meaning. This will assist underlying applications to present analysts with correct feeds for a particular event for fusion. We argue annotated stored feeds will assist in easy retrieval of historical data that may be related to the current fusion. We use a subset of Web Ontology Language (OWL),1 OWL-DL to present a lightweight and efficient knowledge layer for feeds annotation and use rules to capture crucial domain concepts. We discuss a solution architecture and provide a proof-of-concept tool to evaluate the proposed approach. We discuss the importance of such an approach with a set of user cases and show how a tool like the one proposed could assist analysts, planners to make better informed decisions.
1. Computational intensive operations are off-loaded to dedicated nodes, preserving the resources in the ISR/ISTAR networks.
2. HTTP services are accessible through a standard set of APIs irrespective of the reasoner technology used.
3. Support for seamless integration of different reasoners into the system.