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| Content Provider | MDPI |
|---|---|
| Author | Qualls, Joseph Russomanno, David J. |
| 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. |
| File Size | 304128 |
| Ending Page | 3204 |
| Page Count | 28 |
| Starting Page | 3177 |
| File Format | |
| e-ISSN | 14248220 |
| DOI | 10.3390/s110303177 |
| Journal | Sensors |
| Issue Number | 3 |
| Volume Number | 11 |
| Language | English |
| Publisher Date | 2011-03-15 |
| Access Restriction | Open |
| Subject Keyword | sensor networks sensor ontology profiling sensors ontological framework |
| Content Type | Text |
| Resource Type | Article |
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