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http://dx.doi.org/10.5391/JKIIS.2016.26.5.361

Intruder Detection System Based on Pyroelectric Infrared Sensor  

Jeong, Yeon-Woo (School of Electronic & Electrical Engineering, Hongik University)
Vo, Huynh Ngoc Bao (School of Electronic & Electrical Engineering, Hongik University)
Cho, Seongwon (School of Electronic & Electrical Engineering, Hongik University)
Cuhng, Sun-Tae (School of Information Communication Electrical Engineering, Soongsil University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.26, no.5, 2016 , pp. 361-367 More about this Journal
Abstract
The intruder detection system using digital PIR sensor has the problem that it can't recognize human correctly. In this paper, we suggest a new intruder detection system based on analog PIR sensor to get around the drawbacks of the digital PIR sensor. The analog type PIR sensor emits the voltage output at various levels whereas the output of the digitial PIR sensor is binary. The signal captured using analog PIR sensor is sampled, and its frequency feature is extracted using FFT or MFCC. The extracted features are used for the input of neural networks. After neural network is trained using various human and pet's intrusion data, it is used for classifying human and pet in the intrusion situation.
Keywords
PIR; Intruder Detection; MFCC; Neural Networks; Object Classification;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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