Abstract
Sensor-mission assignment involves the allocation of sensor and other information-providing resources to missions in order to cover the information needs of the individual tasks in each mission. This is an important problem in the intelligence, surveillance, and reconnaissance (ISR) domain, where sensors are typically over-subscribed, and task requirements change dynamically. This paper approaches the sensor-mission assignment problem from a Semantic Web perspective: the core of the approach is a set of ontologies describing mission tasks, sensors, and deployment platforms. Semantic reasoning is used to recommend collections of types of sensors and platforms that are known to be “fit-for-purpose” for a particular task, during the mission planning process. These recommended solutions are used to constrain a search for available instances of sensors and platforms that can be allocated at mission execution-time to the relevant tasks. An interface to the physical sensor environment allows the instances to be configured to operate as a coherent whole and deliver the necessary data to users. Feedback loops exist throughout, allowing re-planning of the sensor-task fitness, reallocation of instances, and reconfiguration of the sensor network.
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Gomez, M. et al. (2008). An Ontology-Centric Approach to Sensor-Mission Assignment. In: Gangemi, A., Euzenat, J. (eds) Knowledge Engineering: Practice and Patterns. EKAW 2008. Lecture Notes in Computer Science(), vol 5268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87696-0_30
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DOI: https://doi.org/10.1007/978-3-540-87696-0_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87695-3
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