title: Ontological problem-solving framework for dynamically configuring sensor systems and algorithms.
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.
authors.affiliation: Department of Electrical and Computer Engineering, Herff College of Engineering, University of Memphis, 3720 Alumni Avenue, Memphis, TN 38152, USA. jqualls@rendermatrix.com
authors.forename: Joseph
authors.initials: J
authors.lastname: Qualls
authors.forename: David J
authors.initials: DJ
authors.lastname: Russomanno
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D011340:Problem Solving; D058998:Remote Sensing Technology / Q000295:instrumentation*; D057386:Search Engine