TY - GEN
T1 - An ontology-centric approach to sensor-mission assignment
AU - Gomez, Mario
AU - Preece, Alun
AU - Johnson, Matthew P.
AU - De Mel, Geeth
AU - Vasconcelos, Wamberto
AU - Gibson, Christopher
AU - Bar-Noy, Amotz
AU - Borowiecki, Konrad
AU - La Porta, Thomas
AU - Pizzocaro, Diego
AU - Rowaihy, Hosam
AU - Pearson, Gavin
AU - Pham, Tien
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=56649103590&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=56649103590&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-87696-0_30
DO - 10.1007/978-3-540-87696-0_30
M3 - Conference contribution
AN - SCOPUS:56649103590
SN - 3540876952
SN - 9783540876953
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 347
EP - 363
BT - Knowledge Engineering
PB - Springer Verlag
T2 - 16th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2008
Y2 - 29 September 2008 through 2 October 2008
ER -