Community intrusion detection system based on wavelet neural network

A community intrusion detection system based on wavelet neural network (WNN) is presented in this paper. This system is composed of ARM (Advanced RISC Machines) data acquisition nodes, wireless mesh network and control centre. The data acquisition node uses sensors to collect information and process...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 2; pp. 1026 - 1030
Main Authors Jing-Wen Tian, Mei-Juan Gao, Ling-Fang He, Shi-Ru Zhou
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Community
Control systems
Data acquisition
Face recognition
Image sensors
Intrusion detection
Neural networks
Reduced instruction set computing
Sensor phenomena and characterization
Wavelet analysis
Wavelet neural network
Wireless mesh networks
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Summary:A community intrusion detection system based on wavelet neural network (WNN) is presented in this paper. This system is composed of ARM (Advanced RISC Machines) data acquisition nodes, wireless mesh network and control centre. The data acquisition node uses sensors to collect information and processes them by image detection algorithm, and then transmits information to control centre with wireless mesh network. When there is abnormal phenomenon, the system starts the camera and the WNN is used to recognize the face image. We adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network, and give the network learning algorithm. With the ability of strong pattern classification and function approach and fast convergence of WNN, the recognition method can truly classify the face. This system resolves the defect and improves the intelligence and alleviates worker's working stress.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212396