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Sensors 2011, 11(9), 8370-8394; doi:10.3390/s110908370
Article

Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions

1,*  and 2
1 Department of Electrical and Computer Engineering, Herff College of Engineering, University of Memphis, 3720 Alumni Avenue, Memphis, TN 38152, USA 2 Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis (IUPUI), 799 W. Michigan St., Indianapolis, IN 46202, USA
* Author to whom correspondence should be addressed.
Received: 6 July 2011 / Revised: 6 August 2011 / Accepted: 25 August 2011 / Published: 29 August 2011
(This article belongs to the Section Physical Sensors)

Abstract

The lack of knowledge models to represent sensor systems, algorithms, and missions makes opportunistically discovering a synthesis of systems and algorithms that can satisfy high-level mission specifications impractical. A novel ontological problem-solving framework has been designed that leverages knowledge models describing sensors, algorithms, and high-level missions to facilitate automated inference of assigning systems to subtasks that may satisfy a given mission specification. To demonstrate the efficacy of the ontological problem-solving architecture, a family of persistence surveillance sensor systems and algorithms has been instantiated in a prototype environment to demonstrate the assignment of systems to subtasks of high-level missions.
Keywords: sensor networks; Sensor Ontology; profiling sensors; mission tasking sensor networks; Sensor Ontology; profiling sensors; mission tasking
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Qualls, J.; Russomanno, D.J. Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions. Sensors 2011, 11, 8370-8394.

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