• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1272-1280
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• 2013

In this paper, we propose an audio surveillance system which can detect and localize dangerous sounds in real-time. The location information about dangerous sounds can render a PTZ camera to be directed so as to catch a snapshot image about the dangerous sound source area and send it to clients instantly. The proposed audio surveillance system firstly detects foreground sounds based on adaptive Gaussian mixture background sound model, and classifies it into one of pre-trained classes of foreground dangerous sounds. For detected dangerous sounds, a sound source localization algorithm based on Dual delay-line algorithm is applied to localize the sound sources. Finally, the proposed system renders a PTZ camera to be oriented towards the dangerous sound source region, and take a snapshot against over the sound source region. Experiment results show that the proposed system can detect foreground dangerous sounds stably and classifies the detected foreground dangerous sounds into correct classes with a precision of 79% while the sound source localization can estimate orientation of the sound source with acceptably small error.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1559-1563
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• 2014

Recently, the prevention of crime using CCTV draws special in accordance with the higher crime incidence rate. Therefore security systems like a CCTV with audio capability are developing for giving an instant alarm. This paper proposes a scream detecting engine from various ambient noises in real environment for surveillance systems. The proposed engine detects scream signals among the various ambient noises using the features extracted in time/frequency domain. The experimental result shows the performance of our engine is very promising in comparison with the traditional engines using the model based features like LPC, LPCC and MFCC. The proposed method has a low computational complexity by using FFT and cross correlation coefficients instead of extracting complex features like LPC, LPCC and MFCC. Therefore the proposed engine can be efficient for audio-based surveillance systems with low SNRs in real field.

• Journal of Platform Technology
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• v.6 no.4
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• pp.11-17
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• 2018

In the smart intelligence information society, there is a possibility that the social dysfunction such as the personal information protection issue and the risk to the electronic surveillance society may be highlighted. In this paper, we refer to various categories and classify electronic surveillance into audio surveillance, visual surveillance, location surveillance, biometric information surveillance, and data surveillance. In order to respond to new electronic surveillance in the intelligent information society, it requires a change of perception that is different from that of the past. This starts with the importance of digital privacy and results in the right to self-determination of personal information. Therefore, in order to preemptively respond to the dysfunctions that may arise in the intelligent information society, it is necessary to further raise the awareness of the civil society to protect information human rights.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.363-370
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• 2008

The surveillance system for urban transit now adapt the newest IT technology. The Surveillance system analyzes the video information from various cameras intelligently and determines the critical status automatically. Other sensors, for example fire sensor and audio sensor are used in the surveillance system for increasing the correctness of surveillance. The surveillance system tries to increase the performance of surveillance by gathering lots of information for the current situation and analyzing them intelligently. IP-Based Integrated system needs the distributed computer system with location and functions. For correctly running this system, a distributed software is needed. In this paper, we study the distributed software for IP-based integrated surveillance system. The required functions, safety and extendability are suggested.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.736-743
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• 2022

Construction workers experience a high rate of fatal incidents from mobile equipment in the industry. One of the major causes is the decline in the acoustic condition of workers due to the constant exposure to construction noise. Previous studies have proposed various ways in which audio sensing and machine learning techniques can be used to track equipment's movement on the construction site but not on the audibility of safety signals. This study develops a novel framework to help automate safety surveillance in the construction site. This is done by detecting the audio sound at a different signal-to-noise ratio of -10db, -5db, 0db, 5db, and 10db to notify the worker of imminent dangers of mobile equipment. The scope of this study is focused on developing a signal processing model to help improve the audible sense of mobile equipment for workers. This study includes three-phase: (a) collect audio data of construction equipment, (b) develop a novel audio-based machine learning model for automated detection of collision hazards to be integrated into intelligent hearing protection devices, and (c) conduct field experiments to investigate the system' efficiency and latency. The outcomes showed that the proposed model detects equipment correctly and can timely notify the workers of hazardous situations.

• Journal of IKEEE
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• v.22 no.3
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• pp.624-629
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• 2018

Classification of moving targets in Pulse Doppler Radar(PDR) for surveillance and reconnaissance purposes is generally carried out based on listening and training experience of Doppler audio signals by radar operator. In this paper, we proposed the automatic classification method to identify the class of moving target with Doppler audio signals using the Mel Frequency Cepstral Coefficients(MFCC) and the Hidden Markov Model(HMM) algorithm which are widely used in speech recognition and the classification performance was analyzed and verified by simulations.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.22 no.4
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• pp.276-283
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• 2012

Objectives: This study was conducted to survey the viewpoints on the material safety data sheets(MSDS) training for safety and health managers(SHMs) and workers. Subjects and Methods: A surveillance was made using a self-reported questionnaire for 78 SHMs and 122 workers to survey their viewpoints on the MSDS training. Survey results were analyzed using the SPSS program(Version 12.0 SPSS Inc., USA). Results: The result of the study shows that there are contrasts with the cognition of SHMs' and workers' on the education of MSDS and the program preference for education efficiency of MSDS. Workers were significantly more interested in the MSDS education than the SHMs did. Workers preferred the education program which is easily to be understood, to voluntarily participate on MSDS education, but SHMs did the quiz program. Also we found that the SHMs wanted to learn the education program via the expert(37.3%) rather than education resources(33.3%) which were served by government or relevant agency. In contrast, workers wanted the audio-visual education program, which is mainly consisted of accident cases (33.3%), rather than periodical education program(22.1%). Conclusions: This study showed that effectiveness of MSDS education was associated with the program served by company, and the education program for the voluntary participation of the workers should be made practical and attractive.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1722-1728
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• 2011

The security issue in urban transit system has been widely considered as the common matters after the fire accident at Daegu subway station. The safe urban transit system is highly demanded because of the vast number of daily passengers, and it is one of the most challenging projects. We introduced a test model for integrated security system for urban transit system and built it at a subway station to demonstrate its performance. This system consists of cameras, sensor network and central monitoring software. We described the smart camera functionality in more detail. The proposed smart camera includes the moving objects recognition module, video analytics, video encoder and server module that transmits video and audio information.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.11-17
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• 2016

In this paper, we proposed a multi-viewer system with multiple HD cameras based AVB(Audio Video Bridge) ethernet cable using IP networking, and FPGA(Xilinx Zynq 702) for bus safety systems. This AVB (IEEE802.1BA) system can be designed for the low latency based on FPGA, and transmit real-time with HD video and audio signals in a vehicle network. The proposed multi-viewer platform can multiplex H.264 video signals from 4 wide-angle HD cameras with existed ethernet 1Gbps. and 2-wire 100Mbps cables. The design of Zynq 702 based low latency to H.264 AVC CODEC was proposed for the minimization of time-delay in the HD video transmission of car area network, too. And the performance of PSNR(Peak Signal-to-noise-ratio) was analyzed with the reference model JM for encoding and decoding results in H.264 AVC CODEC. These PSNR values can be confirmed according the theoretical and HW result from the signal of H.264 AVC CODEC based on Zynq 702 the multi-viewer with multiple cameras. As a result, proposed AVB multi-viewer platform with multiple cameras can be used for the surveillance of audio and video around a bus for the safety due to the low latency of H.264 AVC CODEC design.