Multimedia Wireless Sensor Networks - LCN
Multimedia Wireless Sensor Networks - LCN
Multimedia Wireless Sensor Networks - LCN
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Context-Aware Data Fusion Framework<br />
‣ Context-Aware Data Fusion<br />
• Top-down Inference<br />
Given context state, select relevant ambiguity-<br />
reducing context attributes (e.g., time, blood<br />
sugar, frequency of getting up from bed)<br />
• Bottom-up Inference<br />
Given a set of context attributes, infer context<br />
states with varying (reported) ambiguities<br />
‣ Dynamic Bayesian Network (DBN)<br />
• Coherent and unified hierarchical<br />
probabilistic framework<br />
• <strong>Sensor</strong>y data representations,<br />
integration and inference<br />
‣ Compute Ambiguity-Reducing Utility:<br />
Situation<br />
Space<br />
Context<br />
State<br />
Context<br />
Attribute<br />
<strong>Sensor</strong>s<br />
R(t‐1) R(t) R(t+1)<br />
S(t‐1) S(t) S(t+1)<br />
<strong>Sensor</strong> Fusion Mediator<br />
B 1 B 2 B m<br />
K N<br />
2 K N<br />
2<br />
R t<br />
R t<br />
V =<br />
max [ p<br />
a<br />
a ] −<br />
min [ p<br />
a<br />
a ]<br />
i<br />
i = 0<br />
∑<br />
j = 0<br />
j<br />
i<br />
i = 0<br />
∑<br />
j = 0<br />
j<br />
i<br />
t<br />
a<br />
i<br />
R<br />
= Context attribute a j = Situation space
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