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Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions
Department of Electrical and Computer Engineering, Herff College of Engineering, University of Memphis, 3720 Alumni Avenue, Memphis, TN 38152, USA
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; in revised form: 6 August 2011 / Accepted: 25 August 2011 / Published: 29 August 2011
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
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MDPI and ACS Style
Qualls, J.; Russomanno, D.J. Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions. Sensors 2011, 11, 8370-8394.
Qualls J, Russomanno DJ. Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions. Sensors. 2011; 11(9):8370-8394.
Qualls, Joseph; Russomanno, David J. 2011. "Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions." Sensors 11, no. 9: 8370-8394.