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Sensors 2011, 11(3), 3177-3204; doi:10.3390/s110303177

Ontological Problem-Solving Framework for Dynamically Configuring Sensor Systems and Algorithms

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: 7 January 2011 / Revised: 4 February 2011 / Accepted: 11 March 2011 / Published: 15 March 2011
(This article belongs to the Special Issue Semantic Sensor Network Technologies and Applications)

Abstract

The deployment of ubiquitous sensor systems and algorithms has led to many challenges, such as matching sensor systems to compatible algorithms which are capable of satisfying a task. Compounding the challenges is the lack of the requisite knowledge models needed to discover sensors and algorithms and to subsequently integrate their capabilities to satisfy a specific task. A novel ontological problem-solving framework has been designed to match sensors to compatible algorithms to form synthesized systems, which are capable of satisfying a task and then assigning the synthesized systems to high-level missions. The approach designed for the ontological problem-solving framework has been instantiated in the context of a persistence surveillance prototype environment, which includes profiling sensor systems and algorithms to demonstrate proof-of-concept principles. Even though the problem-solving approach was instantiated with profiling sensor systems and algorithms, the ontological framework may be useful with other heterogeneous sensing-system environments. View Full-Text
Keywords: sensor networks; sensor ontology; profiling sensors; ontological framework sensor networks; sensor ontology; profiling sensors; ontological framework
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Qualls, J.; Russomanno, D.J. Ontological Problem-Solving Framework for Dynamically Configuring Sensor Systems and Algorithms. Sensors 2011, 11, 3177-3204.

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