DocumentCode
2138236
Title
Sensor based Environment Adaptive Learning System for Person Authorization
Author
Lee, Young-Ho ; Lee, Kang-Dae ; Chung, Kyung-Yong ; Nam, Mi Young ; Kang, Un-Gu
Volume
3
fYear
2008
fDate
13-15 Dec. 2008
Firstpage
100
Lastpage
103
Abstract
This paper presents a robust distributed architecture for adaptive and intelligent systems, called EAS (environment adaptive learning scheme), with self-learning capability to use under dynamic and uneven environments. Our proposed system adopts the concepts of situation-awareness with the evolutionary computations where the working environments are modeled and identified as environmental situations. We have used ART2 for environment modeling while unsupervised learning algorithm for environment identification. Environment adaptive algorithm, for its adaptive criteria, is used to explore action configuration for each identified situation to implement our concept. We have achieved very encouraging experimental results for CCD camera visual sensor based face detection, recognition system and ECG sensor system.
Keywords
ART neural nets; authorisation; evolutionary computation; knowledge based systems; learning (artificial intelligence); ubiquitous computing; ART2 neural network; CCD camera visual sensor-based face detection; ECG sensor system; environment identification; environment modeling; evolutionary computation; face recognition system; intelligent knowledge based system; person authorization; robust distributed architecture; self-learning capability; sensor-based environment adaptive learning system; situation awareness; ubiquitous system; unsupervised learning algorithm; Adaptive systems; Authorization; Computer architecture; Evolutionary computation; Intelligent sensors; Intelligent systems; Learning systems; Robustness; Sensor systems; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Future Generation Communication and Networking, 2008. FGCN '08. Second International Conference on
Conference_Location
Hainan Island
Print_ISBN
978-0-7695-3431-2
Type
conf
DOI
10.1109/FGCN.2008.228
Filename
4734288
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