• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.703-704
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• 2023

학교폭력은 교육 환경에서 심각한 문제이다. 피해자에게 심리적 고통과 육체적 상해를 입히고 학교 내 안전과 안정성을 위협한다. 이에 많은 교육기관과 정부 기관이 학교폭력 예방과 대처를 위한 다양한 방안을 제시하고 있지만, 여전히 어려운 문제이다. 최근에는 인공지능 기술을 활용하여 학교폭력 방지와 대처에 관한 연구가 이루어지고 있다. 본 연구에서는 YOLOv5(You Only Look Once version 5) 딥러닝 알고리즘을 활용하여 학교 내부에서 발생하는 폭력 행위를 실시간으로 탐지하는 모델을 제안한다. 이 모델은 CCTV와 같은 영상 데이터를 입력으로 받아들여 학교 내부에서 발생하는 폭력 행위를 실시간으로 식별하는 것을 목표로 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.245-247
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• 2022

컨테이너선에서 스위치보드와 리퍼컨테이너의화재 발생 전과 후를 CCTV 및 열화상카메라, 추가센서류로 상시 모니터링하여, 화재 전 이상감지와 화재 후 불꽃, 연기 등의 화재 종류를 선내 알림하여 즉시 조치할 수 있도록 효율적인 화물관리시스템을 설계하고, 정확도 높은 화재 감지를 목적으로 데이터 학습을 위한 영상 및 전류 데이터 수집과 실제 컨테이너 스위치보드 및 리퍼컨테이너 레이아웃을 모사한 Testbed를 구축하였습니다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.321-322
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• 2023

현재 우리 군은 다가오는 인구절벽에 대비하기 위해 인공지능(AI) 기반의 과학기술강군 육성을 목표 국방혁신 4.0을 추진중에 있다. 특히 북한의 도발위협이 높아지는 현시점에 우리 군은 첨단기술을 활용한 과학화경계시스템 도입을 통해 병력절감을 도모하고 있다. 하지만 우리 군의 통합 전투능력을 보장하기 위한 핵심 기반통신체계인 전술정보통신체계(TICN)의 경우 전송 대역폭이 좁아 영상정보 송수신이 원활하지 않을뿐더러 보안 및 난청지역 발생 등의 이유로 평시 과학화경계시스템의 기반 네트워크로 활용하기에는 제한적이다. 이러한 문제를 해결하기 위해 본 논문은 2017년부터 국내에서 무료로 활용할 수 있게 된 TVWS 기반의 무선네트워크 구축 기술을 활용해 TVWS 기반 과학화경계시스템 구축방안을 제안한다. 본 논문에서 제안하는 TVWS 기반 과학화경계시스템의 경우 기존의 유선네트워크 기반의 과학화경계시스템과 비교해 작전공백 최소화, 구축비용 절감, 설치 및 운용의 탄력성 측면에서 다양한 장점을 가진다.

• Annual Conference of KIPS
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• 2007.05a
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• pp.1303-1305
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• 2007

현재 정보통신 기술의 발달에 상응하여 지능형 교통 시스템(ITS)은 네트워크 기반으로 실시간 교통 정보를 제공하기 위해 CCTV, GPS, VDS, 루프 검지기, 영상 검지기 등과 같은 다양한 방법으로 교통 정보 수집이 이루어지고 있다. 또한 정확한 정보 제공을 위해 정보의 수집 및 가공에 대한 많은 연구들이 진행되고 있다. 본 논문에서는 텔레매틱스 기반의 효율적인 교통정보 수집을 위해 RFID 태그 정보를 이용하여 교통정보를 수집하여 보다 정확한 실시간 차량 정보를 제공하는 교통정보 수집 시스템에 관한 연구를 기술하고자 한다.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.27-36
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• 2017

In almost industries, such as the logistics industry, marine fisheries, agriculture, industry, and services, small unmanned aerial vehicles are used for aerial photographing or closing flight in areas where human access is difficult or CCTV is not installed. Also, based on the information of small unmanned aerial photographing, application research is actively carried out to efficiently perform surveillance, control, or management. In order to carry out tasks in a mission-based manner in which the set tasks are assigned and the tasks are automatically performed, the small unmanned aerial vehicles must not only fly steadily but also be able to charge the energy periodically, In addition, the unmanned aircraft need to land automatically and precisely at certain points after the end of the mission. In order to accomplish this, an automatic precision landing method that leads landing by continuously detecting and recognizing a marker located at a landing point from a video shot of a small UAV is required. In this paper, it is shown that accurate and stable automatic landing is possible even if simple template matching technique is applied without using various recognition methods that require high specification in using low cost general purpose small unmanned aerial vehicle. Through simulation and actual experiments, the results show that the proposed method will be made good use of industrial fields.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.725-735
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• 2022

Currently, disasters occurring in Korea are characterized by unpredictability and complexity. Due to these features, property damage and human casualties are increasing. Since the initial response process of these disasters is directly related to the scale and the spread of damage, optimal decision-making is essential, and information of the site must be obtained through timely applicable sensors. However, it is difficult to make appropriate decisions because indiscriminate information is collected rather than necessary information in the currently operated Disaster and Safety Situation Office. In order to improve the current situation, this study proposed a framework that quickly collects various disaster image information, extracts information required to support decision-making, and utilizes it. To this end, a web-based display system and a smartphone application were proposed. Data were collected close to real time, and various analysis results were shared. Moreover, the capability of supporting decision-making was reviewed based on images of actual disaster sites acquired through CCTV, smartphones, and UAVs. In addition to the reviewed capability, it is expected that effective disaster management can be contributed if institutional mitigation of the acquisition and sharing of disaster-related data can be achieved together.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.590-599
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• 2017

In South Korea, sewage pipeline exploration devices have been developed using high resolution digital cameras of 2 mega-pixels or more. On the other hand, most devices are less than 300 kilo-pixels. Moreover, because 100 kilo-pixels devices are used widely, the environment for image processing is very poor. In this study, very low resolution ($240{\times}320$ = 76,800 pixels) images were adapted when it is difficult to detect cracks. Considering that the images of sewers in South Korea have very low resolution, this study selected low resolution images to be investigated. An automatic crack detection technique was studied using digital image processing technology for low resolution images of sewage pipelines. The authors developed a program to automatically detect cracks as 6 steps based on the MATLAB functions. In this study, the second step covers an algorithm developed to find the optimal threshold value, and the fifth step deals with an algorithm to determine cracks. In step 2, Otsu's threshold for images with a white caption was higher than that for an image without caption. Therefore, the optimal threshold was found by decreasing the Otsu threshold by 0.01 from the beginning. Step 5 presents an algorithm that detects cracks by judging that the length is 10 mm (40 pixels) or more and the width is 1 mm (4 pixels) or more. As a result, the crack detection performance was good despite the very low-resolution images.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.77-83
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• 2020

Recently, intelligent predictive surveillance system has emerged. It is a system that can probabilistically predict the future situation and event based on the existing data beyond the scope of the current object or object motion and situation recognition. Since such intelligent predictive monitoring system has a high possibility of handling personal information, security consideration is essential for protecting personal information. The existing video surveillance framework has limitations in terms of privacy. In this paper, we proposed a security framework for intelligent predictive surveillance system. In the proposed method, detailed components for each unit are specified by dividing them into terminals, transmission, monitoring, and monitoring layers. In particular, it supports active personal information protection in the video surveillance process by supporting detailed access control and de-identification.

• Journal of IKEEE
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• v.23 no.2
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• pp.358-363
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• 2019

In this paper, we implemented a welfare system for the elderly living alone, disabled, or babies to provide fast incident response in case of emergency situations. The proposed system can quickly recognize emergency situations using heart rate sensors and real-time image sharing. The sensors attached on a wrist band monitor the heart rate along with relevant bio signals of clients and send alarms to guardians in the emergency situations. At the same time, the real-time image signals are captured using OpenCV and sent to the guardians in order to give the exact information for fast and appropriate response to handle the situation. In the proposed system, the camera works only in the emergency situations so as to provide enough privacy to the client's every day life.