Qualls, JosephRussomanno, David J.2018-07-272018-07-272011-03-15Qualls, J., & Russomanno, D. J. (2011). Ontological Problem-Solving Framework for Dynamically Configuring Sensor Systems and Algorithms. Sensors, 11(3), 3177–3204. https://doi.org/10.3390/s110303177https://hdl.handle.net/1805/16868The 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.en-USAttribution 3.0 United Statessensor networkssensor ontologyprofiling sensorsontological frameworkArticle