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| 삼각검증 센서 데이터 수집× | 센서 융합× | |
|---|---|---|
| 분야≠ | 조사방법론 | 데이터 융합 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1980s–1990s (formalized in sensor fusion and IoT research) | 2013 |
| 창시자≠ | Hall & Llinas and the multisensor data fusion community | Khaleghi, Khamis, Karray & Razavi |
| 유형≠ | Quantitative data collection technique | Multi-source information integration pipeline |
| 원전≠ | Hall, D. L., & Llinas, J. (Eds.). (1997). Handbook of Multisensor Data Fusion. CRC Press. ISBN: 978-0849323798 | Khaleghi, B., Khamis, A., Karray, F. O., & Razavi, S. N. (2013). Multisensor data fusion: A review of the state-of-the-art. Information Fusion, 14(1), 28–44. DOI ↗ |
| 별칭 | multi-sensor triangulation, sensor fusion data collection, redundant sensor sampling, cross-sensor validation | Multisensor Data Fusion, Multi-Sensor Integration, Information Fusion, Sensör Füzyonu |
| 관련≠ | 2 | 3 |
| 요약≠ | Triangulated sensor data collection deploys two or more independent sensors measuring the same phenomenon simultaneously, then cross-validates and aggregates their readings to obtain data that is more accurate, robust, and trustworthy than any single sensor alone. Widely used in environmental monitoring, structural health monitoring, IoT systems, and field experiments, the approach borrows the logic of triangulation from research methodology — using multiple independent sources to converge on a more reliable measurement. | Sensor fusion is a computational process that combines data from multiple heterogeneous sensors to produce an estimate of the environment that is more accurate, complete, and reliable than any single source alone. Systematized as a formal field by Khaleghi, Khamis, Karray, and Razavi in their 2013 state-of-the-art review in Information Fusion, the discipline addresses imperfections such as noise, incompleteness, temporal misalignment, and conflicting readings that arise whenever multiple sensing modalities operate in parallel. |
| ScholarGate데이터셋 ↗ |
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