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

More documents

Recommendations

Info

Future Research • Develop method for distinguishing packet loss from packet delay and determine optimal time between iterations of mote-FVF • Develop self-calibration algorithm • Implement mote-FVF with more sensor information (occupancy sensor, actuation state, etc.) • Distribute mote-FVF algorithm to motes and implement decentralized sensor network • Derive statistical model, implement and compare mote-FVF with model-based approach.
Majority Voting (Correlation among Sensor Readings) • Median value approach – Filter out readings out of the physical limitations of sensor – Take median of the remaining readings • Gaussian correlation approach – Filter out readings out of the physical limitations of sensor – Generate Gaussian functions centered at each reading – Take the reading corresponding to the maximum of the normalized summation of all Gaussian functions
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 and 10: How Fuzzy Validation and Fusion Ove
Page 11 and 12: Mote-FVF Validation • Fuzzy rules
Page 13 and 14: Mote-FVF Prediction • Fuzzy rule
Page 15 and 16: Comparison of Fusion Algorithms Tru
Page 17: Conclusion • Sensor aspect - Phot
Page 21: Mote-based Actuation Architecture A

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

Create successful ePaper yourself

Delete template?

Save as template?