• Title/Summary/Keyword: false alarms

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For the efficient management of electronic security system false alams Study on hybrid Crime sensor (기계경비시스템 오경보의 효율적 관리를 위한 복합형 방범센서에 관한 연구)

  • Kim, Min Su;Lee, DongHwi
    • Convergence Security Journal
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    • v.12 no.5
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    • pp.71-77
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    • 2012
  • Expenses in the form of personnel expenses in the past, in modern times, machine guards to gradually transition has been. This is because the machine guard is more efficient than personnel expenses. But due to false alarms, despite the high expectations of the effects of electronic security in the operation of the electronic security system due to factors that hinder the development of machine guards growth slows. Defect removal aspects of this paper, using IPA (Importance Performance Analysis) techniques to study the operation of electronic security systems and its importance in the development of machine guards, look at how high the technical aspects of electronic security systems composite type of malfunction to minimize crime sensor are presented.

Deep Learning Object Detection to Clearly Differentiate Between Pedestrians and Motorcycles in Tunnel Environment Using YOLOv3 and Kernelized Correlation Filters

  • Mun, Sungchul;Nguyen, Manh Dung;Kweon, Seokkyu;Bae, Young Hoon
    • Journal of Broadcast Engineering
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    • v.24 no.7
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    • pp.1266-1275
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    • 2019
  • With increasing criminal rates and number of CCTVs, much attention has been paid to intelligent surveillance system on the horizon. Object detection and tracking algorithms have been developed to reduce false alarms and accurately help security agents immediately response to undesirable changes in video clips such as crimes and accidents. Many studies have proposed a variety of algorithms to improve accuracy of detecting and tracking objects outside tunnels. The proposed methods might not work well in a tunnel because of low illuminance significantly susceptible to tail and warning lights of driving vehicles. The detection performance has rarely been tested against the tunnel environment. This study investigated a feasibility of object detection and tracking in an actual tunnel environment by utilizing YOLOv3 and Kernelized Correlation Filter. We tested 40 actual video clips to differentiate pedestrians and motorcycles to evaluate the performance of our algorithm. The experimental results showed significant difference in detection between pedestrians and motorcycles without false positive rates. Our findings are expected to provide a stepping stone of developing efficient detection algorithms suitable for tunnel environment and encouraging other researchers to glean reliable tracking data for smarter and safer City.

Performance Analysis of Handover Trigger Based on Signal Strength Measurement (신호 강도 측정 기반 핸드오버 결정 방법의 성능 분석)

  • Park, Jae-Sung;Lim, Yu-Jin
    • The KIPS Transactions:PartC
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    • v.14C no.7
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    • pp.603-610
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    • 2007
  • Effective handover decision is important for providing seamless services to mobile users. In this paper, we propose an analysis framework to evaluate the performance of handover decision based on received signal strength (RSS) measurements in terms of the late notification and false alarm probability. In our framework, we consider mobility of a mobile user, signaling delays for exchanging messages related to handover protocols, cell sizes and RSS measurement interval to stabilize RSS reading due to random measurement errors. By quantitatively scrutinizing the impact of each parameter on the late notification and false alarms, we suggest the research directions for effective handover decision mechanism that may provide fast and reliable handover.

Height Prediction Mechanism for Smart Surveillance Systems (지능형 보안 감시 시스템을 위한 높이 예측 메커니즘)

  • Shim, Jaeseok;Lim, Yujin
    • KIPS Transactions on Computer and Communication Systems
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    • v.3 no.7
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    • pp.241-244
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    • 2014
  • Wireless Sensor Network(WSN) has been attracting lots of interest in recent years for smart surveillance systems. WSN-based surveillance systems need to figure out the occurrence or existence of events or objects and to find out where the events have occurred or the objects are present. In our surveillance system, it is needed to give an alarm only when the detected object is human (not pets or rodents) for reducing false alarms and improving the system reliability. In this paper, we propose a height prediction mechanism to determine if the detected object is human using Heron's formula. Finally, we verify the performance of our proposed mechanism through various experiments.

Face Detection based on Matched Filtering with Mobile Device (모바일 기기를 이용한 정합필터 기반의 얼굴 검출)

  • Yeom, Seok-Won;Lee, Dong-Su
    • Journal of the Institute of Convergence Signal Processing
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    • v.15 no.3
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    • pp.76-79
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    • 2014
  • Face recognition is very challenging because of the unexpected changes of pose, expression, and illumination. Facial detection in the mobile environments has additional difficulty since the computational resources are very limited. This paper discusses face detection based on frequency domain matched filtering in the mobile environments. Face detection is performed by a linear or phase-only matched filter and sequential verification stages. The candidate window regions are selected by a number of peaks of the matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering tests, which aim to remove false alarms among selected candidate windows. The algorithms are built with JAVA language on the mobile device operated by the Android platform. The simulation and experimental results show that real-time face detection can be performed successfully in the mobile environments.

Development of Smart Device Module for Perimeter Intrusion Detection (외곽 침입 감지를 위한 스마트 디바이스의 개발)

  • Ryu, Dae-Hyun;Choi, Tae-Wan
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.2
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    • pp.363-370
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    • 2021
  • The perimeter intrusion detection system is very important in physical security. In this study, a micro smart device (module) using MEMS sensor was developed in IoT environment for external intrusion detection. The outer intrusion detection system applying the smart device developed in this study is installed in various installation environments, such as barbed wire of various materials and shapes, the city center, the beach, and the mountain, so that it can detect external intrusion and its location as well as false alarms. As a smart sensor that can minimize the false alarm rate and economical construction cost, it is expected that it can be used for the safe operation of major facilities and prevention of disasters and crimes.

Four Segmentalized CBD Method Using Maximum Contrast Value to Improve Detection in the Presence of Reverberation (최대 컨트라스트 값을 이용한 4분할 CBD의 잔향 감소기법)

  • Choi, Jun-Hyeok;Yoon, Kyung-Sik;Lee, Soo-Hyung;Kwon, Bum-Soo;Lee, Kyun-Kyung
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.8
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    • pp.761-767
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    • 2009
  • The detection of target echoes in a sonar image is usually difficult since reverberation is originated by the returns reflected around the boundary and volumes. Under the scenario of the target presence around the reverberation, the detection performance of existing algorithms is degraded. Since they have a similar statistical features. But proposed detector gives improvement existing algorithms Under this scenario. In this paper, 4 segmentation contrast box algorithm using maximum contrast value is proposed based on statistical segmentation, which gives better detection performance in the sense of reducing false alarms. The simulations validate the effectiveness of the proposed algorithm.

A Study on the Causes of False Alarm by NFPA921 in Semiconductor Factory (반도체공장의 NFPA921에 의한 비화재보 원인조사 방안)

  • Sang-Hyuk Hong;Ha-Sung Kong
    • Journal of the Korea Safety Management & Science
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    • v.25 no.4
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    • pp.87-94
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    • 2023
  • This study analyzed and identified various causes of caustic alarms of 163 fire detectors that occurred from January 2019 to December 2021 at domestic semiconductor manufacturing plants equipped with about 30,000 fire detectors, and proposed a new non-fire prevention cause investigation plan by applying the NFPA 921 scientific methodology. The results of the study are as follows. First, in terms of necessary recognition and problem definition, an analog detector and an integrated monitoring system were proposed to quickly determine the location and installation space information of the fire detector. Second, in order to prevent speculative causes and errors in various analyses in terms of data analysis and hypothesis establishment, non-fire reports were classified into five by factor and defined, and the causes of occurrence by factor were classified and proposed. Finally, in terms of hypothesis verification and final hypothesis selection, a non-fire prevention improvement termination process and a final hypothesis verification sheet were proposed to prevent the cause from causing re-error.

Key Re-distribution Scheme of Dynamic Filtering Utilizing Attack Information for Improving Energy Efficiency in WSNs (무선 센서 네트워크에서 에너지 효율성 향상을 위해 공격정보를 활용한 동적 여과 기법의 키 재분배 기법)

  • Park, Dong-Jin;Cho, Tae-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.2
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    • pp.113-119
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    • 2016
  • Wireless sensor networks are vulnerable to an adversary due to scarce resources and wireless communication. An adversary can compromise a sensor node and launch a variety of attacks such as false report injection attacks. This attack may cause monetary damage resulting in energy drain by forwarding the false reports and false alarms at the base station. In order to address this problem, a number of en-route filtering schemes has been proposed. Notably, a dynamic en-route filtering scheme can save energy by filtering of the false report. In the key dissemination phase of the existing scheme, the nodes closer to the source node may not have matching keys to detect the false report. Therefore, continuous attacks may result in unnecessary energy wastage. In this paper, we propose a key re-distribution scheme to solve this issue. The proposed scheme early detects the false report injection attacks using initially assigned secret keys in the phase of the key pre-distribution. The experimental results demonstrate the validity of our scheme with energy efficiency of up to 26.63% and filtering capacity up to 15.92% as compared to the existing scheme.

Regional Path Re-selection Period Determination Method for the Energy Efficient Network Management in Sensor Networks applied SEF (통계적 여과 기법이 적용된 센서 네트워크에서 에너지 효율적인 네트워크 관리를 위한 영역별 경로 재설정 주기 결정 기법)

  • Park, Hyuk;Cho, Tae-Ho
    • Journal of the Korea Society for Simulation
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    • v.20 no.3
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    • pp.69-78
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    • 2011
  • A large-scale sensor network usually operates in open and unattended environments, hence individual sensor node is vulnerable to various attacks. Therefore, malicious attackers can physically capture sensor nodes and inject false reports into the network easily through compromised nodes. These false reports are forwarded to the base station. The false report injection attack causes not only false alarms, but also the depletion of the restricted energy resources in a battery powered network. The statistical en-route filtering (SEF) mechanism was proposed to detect and drop false reports en route. In SEF, the choice of routing paths largely affect the energy consumption rate and the detecting power of the false report. To sustain the secure routing path, when and how to execute the path re-selection is greatly need by reason of the frequent network topology change and the nodes's limitations. In this paper, the regional path re-selection period determination method is proposed for efficient usage of the limited energy resource. A fuzzy logic system is exploited in order to dynamically determine the path re-selection period and compose the routing path. The simulation results show that up to 50% of the energy is saved by applying the proposed method.