• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.243-250
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• 2018

This paper designs and implements a smart care system for the senior citizen who lives alone. Recently, as the level of living has increased due to the rapid improvement of medicine, living standard and environment, the proportion of the elderly population is increasing. In addition, the proportion of the elderly living alone, which is increasing with the aging society, suggests that the provision of services such as the elder care system and emergency notification is becoming an important issue. However, since the existing emergency notification technology analyzes fixed CCTV images, it is difficult to monitor in the blind spot of CCTV and to move to a place where the camera is not installed. There is a problem that it can not be performed. Therefore, in this paper, we design and develop a smart care system that utilizes robot and object tracking technology that can move in real time to overcome these shortcomings. This enables real-time monitoring regardless of the location, and prompts for assistance in case of an emergency, so that it can provide convenience to cares and assistants.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.12
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• pp.947-954
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• 2017

In case of a fire in urban large structures such as super high-rise buildings, evacuation guidance must be provided to the occupants in order to minimize human deaths and injuries. Therefore, it is essential to provide emergency evacuation guidance when a major fire occurs. In order to effectively support evacuation guidance, it is important to identify major items such as fire location, occupant position, escape route, etc. Also, it is important to quickly identify evacuation areas where residents can safely evacuate from a fire. In this paper, we analyze the CCTV video and propose a method of measuring visibility of the evacuation zone from the smoke caused by the fire in order to determine the safety of evacuation area. To do this, we first extract the background video from the smoke video to measure the visibility of the specific area due to smoke. After generating an edge-extracted image for the extracted background video, the degree of visibility is measured by calculating the change in the edge strength due to smoke.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6420-6426
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• 2013

The indoor areas for the commercial use of automatic monitoring systems of mobile robot localization improves the cognitive abilities and the needs of the environment with this emerging and existing mobile robot localization, and object recognition methods commonly around its great sensor are leveraged. On the other hand, there is a difficulty with a problem-solving self-location estimation in indoor mobile robots using only the sensors of the robot. Therefore, in this paper, a self-position estimation method for an enhanced and effective mobile robot is proposed using a marker and CCTV video that is already installed in the building. In particular, after recognizing a square mobile robot and the object from the input image, and the vertices were confirmed, the feature points of the marker were found, and marker recognition was then performed. First, a self-position estimation of the mobile robot was performed according to the relationship of the image marker and a coordinate transformation was performed. In particular, the estimation was converted to an absolute coordinate value based on CCTV information, such as robots and obstacles. The study results can be used to make a convenient self-position estimation of the robot in the indoor areas to verify the self-position estimation method of the mobile robot. In addition, experimental operation was performed based on the actual robot system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.547-557
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• 2016

Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.771-783
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• 2012

This paper proposes a scheme to collect video data of the vehicle black box in order to strengthen the public safety. The existing schemes, such as surveillance system with the fixed CCTV and car black box, have privacy issues, network traffic overhead and the storage space problems because all video data are sent to the central server. In this paper, the central server only collects the video data related to the accident or the criminal offense using the GPS information and time in order to investigation of the accident or the criminal offense. The proposed scheme addresses the privacy issues and reduces network traffic overhead and the storage space of the central server since the central server collects the video data only related to the accident and the criminal offense. The implementation and experiment shows that our service is feasible. The proposed service can be used as a component of remote surveillance system to prevent the criminal offense and to investigate the criminal offense.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.599-606
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• 2015

International Hydrographic Organization(IHO) adopted standard S-100 as the international standard Geographic Information System(GIS) that can be generally used in the maritime sector. Accordingly, the next-generation system to support navigation information based on GIS standard technology has being developed. AR based navigation information system that supported navigation by overlapping navigation information on the CCTV image has currently being developed. In this study, we considered the application of a transparent display as a method to support efficiently this system. When a transparent display applied, the image distortion caused by using a wide-angle lens for parallax secure, and the disc s, and demonstrated the applicability of the technology by developing a prototype.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.37 no.4
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• pp.337-344
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• 2004

A real-time surveillance system of the inshore fishing ground was constructed to identify and detect discrete targets, such as illegal fishing vessels. This paper describes measurements made with a combination of sensors, such as radar, CCTV camera, and GPS receivers, for monitoring the fishing activity of small vessels within the fishing limit zones of the inshore waters. The CCTV camera system was used to confirm detection and to classify the type of target. The location of legal vessels distributed in coastal waters was acquired from each GPS system of ships connected to commercial satellite communication network. The surveillance system was networked via LAN to one host PC with the use of electronic navigational charts (ENC) and a radar link. Radar Target Extractor (RTX) for radar signal processing can be remotely accessed and controlled on existing PC via the internet, from anywhere, at any time. Results are presented that demonstrate the effectiveness of the newly constructed fisheries monitoring system for conducting continuous surveillance of illegal fishing vessels in the inshore fishing ground. The identification of illegal fishing vessels was achieved by comparing radar positions of illegal fishing vessels exceeding the warning limits in the surveillance area with GPS position reports transmitted from legal fishing vessels, and the illegal fishing vessels were marked with red symbols on the ENC screen of a PC. The methods to track the activities of all vessels intruding or leaving the fishing limit zones also were discussed.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.397-408
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• 2021

The construction industry has the highest occupational accidents/injuries and has experienced the most fatalities among entire industries. Korean government installed surveillance camera systems at construction sites to reduce occupational accident rates. Construction safety managers are monitoring potential hazards at the sites through surveillance system; however, the human capability of monitoring surveillance system with their own eyes has critical issues. A long-time monitoring surveillance system causes high physical fatigue and has limitations in grasping all accidents in real-time. Therefore, this study aims to build a deep learning-based safety monitoring system that can obtain information on the recognition, location, identification of workers and heavy equipment in the construction sites by applying multiple object tracking with instance segmentation. To evaluate the system's performance, we utilized the Microsoft common objects in context and the multiple object tracking challenge metrics. These results prove that it is optimal for efficiently automating monitoring surveillance system task at construction sites.

• Journal of Cadastre & Land InformatiX
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• v.44 no.1
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• pp.139-150
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• 2014

Recently the violent crimes is the emerging social issue and the crime prevention is important policy both for maintenance of public order and the national welfare. To prevent these crimes with the geospatial data, we study the geospatial crime DB features, analytical method and linking method of current National Police Agency's crime system data. In this study, the Geospatial Information Open Platform(Vworld) was used to map the test site crime DB on the thematic map. We also researched the mesh-up thematic map and optimal location model of petrol car and CCTV.