Qualls, JosephRussomanno, David J.2018-07-272018-07-272011-08-29Qualls, J., & Russomanno, D. J. (2011). Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions. Sensors (Basel, Switzerland), 11(9), 8370–8394. https://doi.org/10.3390/s1109083701424-8220https://hdl.handle.net/1805/16860The 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.en-USAttribution 3.0 United Statessensor networksSensor Ontologyprofiling sensorsmission taskingArticle