• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2170-2190
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• 2012

There are nowadays strong demands for intelligent surveillance systems, which can infer or understand more complex behavior. The application of crowd density estimation methods could lead to a better understanding of crowd behavior, improved design of the built environment, and increased pedestrian safety. In this paper, we propose a new crowd density estimation method, which aims at estimating not only a moving crowd, but also a stationary crowd, using images captured from surveillance cameras situated in various public locations. The crowd density of the moving people is measured, based on the moving area during a specified time period. The moving area is defined as the area where the magnitude of the accumulated optical flow exceeds a predefined threshold. In contrast, the stationary crowd density is estimated from the coarseness of textures, under the assumption that each person can be regarded as a textural unit. A multilayer neural network is designed, to classify crowd density levels into 5 classes. Finally, the proposed method is experimented with PETS 2009 and the platform of Gangnam subway station image sequences.

• Journal of Information Processing Systems
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• 제8권3호
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• pp.471-482
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• 2012

For disaster exploration and surveillance application, this paper aims to present a novel application of a multi-robot agent based on WSN and to evaluate a multi-hop communication caused by the robotics correspondingly, which are used in the uncertain and unknown subterranean tunnel. A Primary-Scout Multi-Robot System (PS-MRS) was proposed. A chain topology in a subterranean environment was implemented using a trimmed ZigBee2006 protocol stack to build the multi-hop communication network. The ZigBee IC-CC2530 modular circuit was adapted by mounting it on the PS-MRS. A physical experiment based on the strategy of PS-MRS was used in this paper to evaluate the efficiency of multi-hop communication and to realize the delivery of data packets in an unknown and uncertain underground laboratory environment.

• 디지털콘텐츠학회 논문지
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• 제18권6호
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• pp.1009-1015
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• 2017

최근 범죄, 테러, 교통, 보안등의 이유로 카메라의 설치가 더욱 많아짐에 따라 비디오 감시가 점점 일반화 되어가고 있다. 설치된 카메라로부터 입력된 비디오는 중앙관제센터에서 멀티스크린으로 모니터링 되고 있고, 처한 상황이나 위험 등으로부터 빠르게 대응하기 위해 실시간으로 여러 화면을 동시에 감시는 것이 필수 요소가 되고 있다. 그러나 멀티스크린 화면으로 스마트폰과 같은 모바일 환경에서 모니터링할 때, 하드웨어 스펙이나, 네트워크 대역폭의 문제로 적용되지 못하고 있다. 따라서 본 논문에서는 스마트폰 환경에서 실시간으로 멀티스크린화면을 감시할 수 있는 시스템을 제안한다. 사용자가 원하는 멀티스크린 화면을 트랜스코딩을 통해 재구성하였고, 스마트폰 환경에서 끊김 없이 복수의 카메라를 모니터링하여, 이동하면서도 감시할 수 있는 장점을 가질 수 있다.

• 융합보안논문지
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• 제19권3호
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• pp.51-59
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• 2019

본 논문에서는 사물인터넷(IoT) 시대의 안전한 기업 내부 네트워크 환경을 유지시키기 위하여 네트워크 가시성을 확보할 수 있는 단말 식별 시스템을 제안한다. 최근 기업 네트워크의 영역은 점점 더 넓어지고 복잡해지고 있다. 더 이상 데스크톱과 스마트폰뿐만 아니라 업무용 패드, 바코드스캐너, AP, Video Surveillance, 디지털 도어, 방범장치, 기타 IoT 장비 등 빠르게 증가하고 있으며, 이에 따라 보안위협 역시 증가하고 있다. 따라서 본 논문에서는 IoT 시대의 폭발적으로 증가하고 있는 단말을 식별할 수 있는 프로세스 및 모듈별 기능을 포함하는 단말 식별 시스템을 제안한다. 제안하는 시스템은 기업의 보안 관리자에게 다양한 단말의 정보 및 취약점 등을 제공하여 사내 네트워크에서 발생할 수 있는 잠재적인 사이버 위협뿐만 아니라 비즈니스 위협에 대응할 수 있는 종합적인 위협 관리 기능을 제공할 수 있다.

• 한국통신학회논문지
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• 제38C권7호
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• pp.551-562
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• 2013

모니터링 관리자가 상주해야 하는 현재 CCTV와 같은 방범시스템은 음영지역 등에서의 범죄를 인식하고 실시간으로 대응하기에 한계가 있다. 이를 보안하기 위해 주변 환경속에서 보고, 듣고, 생각하는 사람처럼 능동적인 행동이 가능한 유기체와 같은 유비쿼터스 센서 네트워크 컴퓨팅 기술을 사용한 지능형 보안감시 시스템의 필요성이 대두 되고 있다. 이에 본 논문에서는 PSD 센서와, Dual PIR 시스템을 통합하여 응용한 능동적 보안감시 시스템을 제안하였다. 제안된 시스템은 침입자 유/무만 확인하던 기존의 실내 보안감시 시스템을 발전시켜 상황인지 기술을 융합하였으며, 주변상황 및 사용자의 의도를 시스템이 독립적으로 인지하여 상황에 따른 대응환경의 구축이 가능케 하였다. 제안된 시스템의 효율성 검증을 위하여 다양한 형태의 시뮬레이션을 수행하였다.

• 한국대기환경학회지
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• 제23권5호
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• pp.526-538
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• 2007

Since air quality monitoring data sets are important base for developing of air quality management strategies including policy making and policy performance assessment, the environmental protection authorities need to organize and operate monitoring network properly. Air quality monitoring network of Busan, consisting of 18 stations, was allocated under unscientific and irrational principles. Thus the current state of air quality monitoring networks was reassessed the effect and appropriateness of monitoring objectives such as population protection and sources surveillance. In the process of the reassessment, a GIS-based decision support system was constructed and used to simulate air quality over complex terrain and to conduct optimization analysis for air quality monitoring network with multi-objective. The maximization of protection capability for population appears to be the most effective and principal objective among various objectives. The relocation of current monitoring stations through optimization analysis of multi-objective appears to be better than the network building for maximization of population protection capability. The decision support system developed in this study on the basis of GIS-based database appear to be useful for the environmental protection authorities to plan and manage air quality monitoring network over complex terrain.

• Journal of information and communication convergence engineering
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• 제9권6호
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• pp.683-688
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• 2011

The wireless sensor network (WSN) is well known for an enabling technology for the ubiquitous environment such as real-time surveillance system, habitat monitoring, home automation and healthcare applications. However, the WSN featuring wireless communication through air, a resource constraints device and irregular network topology, is threatened by malicious nodes such as eavesdropping, forgery, illegal modification or denial of services. For this reason, security in the WSN is key factor for utilizing the sensor network into the commercial way. There is a series of symmetric cryptography proposed by laboratory or industry for a long time. Among of them, recently proposed HUMMINGBIRD algorithm, motivated by the design of the well-known Enigma machine, is much more suitable to resource constrained devices, including smart card, sensor node and RFID tags in terms of computational complexity and block size. It also provides resistance to the most common attacks such as linear and differential cryptanalysis. In this paper, we implements ultra-lightweight cryptography, HUMMINGBIRD algorithm into the resource constrained device, sensor node as a perfectly customized design of sensor node.

• Journal of information and communication convergence engineering
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• 제11권1호
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• pp.12-16
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• 2013

Sensor network is one of the strongest technologies for various applications including home automation, surveillance system and monitoring system. To ensure secure and robust network communication between sensor nodes, plain-text should be encrypted using encryption methods. However due to their limited computation power and storage, it is difficult to implement public key cryptography, including elliptic curve cryptography, RSA and pairing cryptography, on sensor networks. However, recent works have shown the possibility that public key cryptography could be made available in a sensor network environment by introducing the efficient multi-precision multiplication method. The previous method suggested a broad rule of multiplication to enhance performance. However, various features of sensor motes have not been considered. For optimized implementation, unique features should be handled. In this paper, we propose a fully optimized multiplication method depending on a different specification for sensor motes. The method improves performance by using more efficient instructions and general purpose registers.

• 한국터널지하공간학회 논문집
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• 제19권5호
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• pp.813-827
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• 2017

터널 내의 CCTV 영상은 동적으로 변화하는 요소들에 의해 영향을 받는 다양한 영상들을 촬영한다. 또한, 카메라의 상태 또한 관리 및 배치가 쉽지 않아 터널 내부 환경 변화에 따라 영상이 달라지는 경향이 있다. 본 논문에서는 터널 내에 설치된 CCTV 카메라 영상을 이용해 차량을 탐지하고 그 차량을 지속적으로 추적하는 새로운 방법을 소개한다. 터널 내 CCTV 카메라 영상은 모션블러 효과와 먼지로 인한 렌즈 흐려짐 효과로 인해 바로 차량을 탐지할 수 없다는 문제점이 있다. 본 논문에서는 이를 극복하기 위해 차영상/비-최대 억제 기법과 Haar Cascade 기법 등에 대한 효과 검토 실험을 제안하고 수행하였다. 본 논문에서 제안하는 방법을 통해 터널 내에 설치된 CCTV에서 차량의 탐지와 추적을 효과적으로 수행할 수 있으며 다양한 터널 유고상황을 자동으로 파악하기 위한 중요 정보를 확보할 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.79-85
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• 2017

In this paper, we propose a CNN-based swimmer detection algorithm. Every year, water safety accidents have been occurred frequently, and accordingly, intelligent video surveillance systems are being developed to prevent accidents. Intelligent video surveillance system is a real-time system that detects objects which users want to do. It classifies or detects objects in real-time using algorithms such as GMM (Gaussian Mixture Model), HOG (Histogram of Oriented Gradients), and SVM (Support Vector Machine). However, HOG has a problem that it cannot accurately detect the swimmer in a complex and dynamic environment such as a beach. In other words, there are many false positives that detect swimmers as waves and false negatives that detect waves as swimmers. To solve this problem, in this paper, we propose a swimmer detection algorithm using CNN (Convolutional Neural Network), specialized for small object sizes, in order to detect dynamic objects and swimmers more accurately and efficiently in complex environment. The proposed CNN sets the size of the input image and the size of the filter used in the convolution operation according to the size of objects. In addition, the aspect ratio of the input is adjusted according to the ratio of detected objects. As a result, experimental results show that the proposed CNN-based swimmer detection method performs better than conventional techniques.