Multimedia Wireless Sensor Networks - LCN
Multimedia Wireless Sensor Networks - LCN
Multimedia Wireless Sensor Networks - LCN
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Novel Contributions: Techniques<br />
‣ Context t model<br />
• Abstraction of raw data into high level contexts<br />
‣ Context aware data fusion<br />
Application Services<br />
• Understanding ambiguity<br />
Satisfy Qualty Requirements<br />
• Dynamic Bayesian <strong>Networks</strong> (DBNs) for ambiguity<br />
resolution<br />
Information Theoretic Reasoning<br />
‣ Intelligent sensor information management<br />
• Information theoretic reasoning<br />
Context Attributes<br />
• Optimal sensor parameter selection<br />
• Reduction in ambiguity/error in state<br />
estimation process<br />
‣ Quality-aware context determination<br />
Context-Aware Data Fusion (DBN)<br />
Raw Data (Vital Signs, Activity, Location)<br />
with noise, uncertainty, ambiguity<br />
<strong>Sensor</strong>s<br />
• Tradeoff communication cost vs. accuracy<br />
‣ Validation with SunSPOT sensor test bed
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