Linganisha mbinu

	Ukusanyaji Data ya Kihisi kwa Njia ya Triangulation	Muunganiko wa Sensorer
Nyanja	Metodolojia ya Dodoso	Uunganishaji wa Data
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1980s–1990s (formalized in sensor fusion and IoT research)	2013
Mwanzilishi	Hall & Llinas and the multisensor data fusion community	Khaleghi, Khamis, Karray & Razavi
Aina	Quantitative data collection technique	Multi-source information integration pipeline
Chanzo asilia	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.
Majina mbadala	multi-sensor triangulation, sensor fusion data collection, redundant sensor sampling, cross-sensor validation	Multisensor Data Fusion, Multi-Sensor Integration, Information Fusion, Sensör Füzyonu
Zinazohusiana	2	3
Muhtasari	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.