An Ontology-Centric Approach to Sensor-Mission Assignment

Mario Gomez, Alun David Preece, Pauline Johnson, Geeth Ranmal De Mel, Wamberto Weber Vasconcelos, Christopher Gibson, Amotz Bar-Noy, Konrad Borowiecki, Thomas La Porta, Diego Pizzocaro, Hosam Rowaihy, Gavin Pearson, Tien Pham

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution


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.

Original languageEnglish
Title of host publicationKnowledge Engineering
Subtitle of host publicationPractice and Patterns
EditorsAldo Gangemi, Jérôme Euzenat
Place of PublicationBerlin, Germany
Number of pages17
ISBN (Print)3540876952, 978-3540876953
Publication statusPublished - 12 Sept 2008
Event16th International Conference, EKAW 2008 - Acitrezza, Italy
Duration: 29 Sept 20082 Oct 2008

Publication series

NameLecture Notes in Artificial Intelligence
ISSN (Print)0302-9743


Conference16th International Conference, EKAW 2008


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