Situation Understanding Based on Heterogeneous Sensor Networks and Human-Inspired Favor Weak Fuzzy Logic System

Humans use multiple sources of sensory information to estimate environmental properties and has innate ability to integrate information from heterogeneous data sources. How the multi-sensory and multimodal information are integrated in human brain? There is consensus that it depends on the prefronta...

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Bibliographic Details
Main Author: Qilian Liang
Format: Conference Proceeding
Language:English
Subjects:
Acoustic sensors
Communications Society
Engines
Eyes
Fuzzy logic
Haptic interfaces
Humans
Image sensors
Sensor systems
Shape
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Summary:Humans use multiple sources of sensory information to estimate environmental properties and has innate ability to integrate information from heterogeneous data sources. How the multi-sensory and multimodal information are integrated in human brain? There is consensus that it depends on the prefrontal cortex (PFC). The PFC has top-down control (favor weak) and rule-based mechanisms, and we incorporate the favor weak mechanism into rule-based fuzzy logic systems (FLS) via using upper and lower membership functions. The inference engine of favor weak fuzzy logic system is proposed under three different categories based on fuzzifiers. We apply the favor weak FLS to situation understanding based on heterogeneous sensor network, and it shows that our favor weak fuzzy logic system has clear advantage comparing to the type-1 FLS. The favor weak FLS can increase the probability of threat detection, and provides timely indication & warning (I&W).
ISSN:1550-3607
1938-1883
DOI:10.1109/ICC.2009.5199462