Glass break detection system using deep auto encoders with fuzzy rules induction algorithm

Nyein Naing, Wai Yan and Htike, Zaw Zaw (2019) Glass break detection system using deep auto encoders with fuzzy rules induction algorithm. International Journal of Advanced and Applied Sciences, 6 (2). pp. 33-38. ISSN 2313-626X E-ISSN 2313-3724

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Abstract

Main uses of glass windows in commercial and residential buildings are prevalent. While a glass-based material has its advantages, it also poses security risks. Therefore, glass break detectors play an important role in security protection for offices and residential buildings. Conventional vibration-based and acoustic-based glass break detectors are designed to detect predetermined temporal and frequency feature thresholds of glass breakage sound signals. This leads to the inability to differentiate glass break from environmental sounds (such as the sound of striking objects, heavy sounds and shouted sounds) that are similar in their amplitude threshold and frequency pattern. Machine learning based acoustic audio classification has been popular in security surveillance applications. Researchers are interested in this research area, and different approaches have been proposed for anomaly event detection (such as gunshots, glass breakage sounds, etc.). This paper proposes a new design of a glass break detection algorithm based on Fuzzy Deep Auto-encoder Neural Network. The algorithm reduces false alarms and improves detection accuracy. Experimental results indicate that proposed fuzzy deep auto-encoder network system attained 95.5% correct detection for the proposed audio dataset.

Item Type:	Article (Journal)
Additional Information:	6919/69673
Uncontrolled Keywords:	Glass break detection, Deep auto-encoder neural network, Fuzzy rule induction algorithm,
Subjects:	Q Science > Q Science (General) > Q300 Cybernetics > Q350 Information theory
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Mr. Zaw Zaw Htike
Date Deposited:	22 Jan 2019 13:45
Last Modified:	12 Mar 2019 16:21
URI:	http://irep.iium.edu.my/id/eprint/69673

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