Smart Dust Sensor Mote Characterization, Validation, Fusion and ...

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Mote-FVF • Mote-FVF (Fuzzy Validation and Fusion) algorithm – Validation • Majority voting • Dynamic centered validation curve generating • Confidence value assigning – Fusion • Weighted averaging – Prediction • Exponential weighted moving average time series predicting
Mote-FVF Validation • Fuzzy rules for validation curve: Def: Cor(x) – the majority voting result Var(x) – the difference between Cor(x) and predicted reading IF Var(x) small THEN move toward the Cor(x) a small amount IF Var(x) medium THEN move toward the Cor(x) a medium amount IF Var(x) large THEN move toward the Cor(x) a large amount Sensor confidence () 1 0.8 0.6 0.4 0.2 0 x ( ) cor x x ˆx Fuzzy validation gate Measurement
Page 1 and 2: Presentation for Master of Science
Page 3 and 4: Intelligent Daylighting Control Sys
Page 5 and 6: Mote Sensor Characterization • Il
Page 7 and 8: BESTnet • BESTnet v. 1.0 - Centra
Page 9: How Fuzzy Validation and Fusion Ove
Page 13 and 14: Mote-FVF Prediction • Fuzzy rule
Page 15 and 16: Comparison of Fusion Algorithms Tru
Page 17 and 18: Conclusion • Sensor aspect - Phot
Page 19 and 20: Majority Voting (Correlation among
Page 21: Mote-based Actuation Architecture A

Smart Dust Sensor Mote Characterization, Validation, Fusion and ...

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